> ## Documentation Index > Fetch the complete documentation index at: https://docs.cognigy.com/llms.txt > Use this file to discover all available pages before exploring further. # AI Agent Updated in 2026.5 AI Agent Node ## Description The AI Agent Node assigns a job to an AI Agent, provides instructions and tools for that job, and access to the knowledge the AI Agent can use when holding a conversation with a user. To configure this Node, follow these steps: 1. [Define an AI Agent job](#parent-node). 2. [Define the tool actions to perform this task](#child-nodes). ## Limitations * By default, the number of transcript turns is set to 50. In the AI Agent Node, this number is fixed and can't be adjusted, unlike in the [LLM Prompt](/ai/agents/develop/node-reference/service/llm-prompt#advanced) and [Get Transcript](https://docs.cognigy.com/ai/agents/develop/node-reference/service/get-transcript#parameters) Nodes, where customization is possible. - The **Description** and **Enum** fields in the **Parameters** section of an [AI Agent tool](#parameters) don't support CognigyScript. ## Parameters ### Parent Node This configuration assigns a job to an AI Agent, defines its role and responsibilities, and provides additional instructions or context to guide its actions. | Parameter | Type | Description | | ------------------------ | ------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | AI Agent | Selector | Select the AI Agent. | | Job Name | CognigyScript | Specify the name of the job. For example, `Customer Support Specialist`. | | Job Description | CognigyScript | Provide a description of the job responsibilities to guide the AI Agent's interactions. For example, `Assist customers with product issues, escalate complex cases, and provide guidance on best practices`. | | Instructions and Context | Toggle | Add specific instructions or context as a system message to help the AI Agent better fulfill the job requirements. For example, `Stay professional and friendly; focus on problem-solving and clarity`. These instructions are considered in addition to those specified in the AI Agent creation settings. | | Parameter | Type | Description | | --------------------------- | ------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Long-Term Memory Injection | Selector | Allow the AI Agent to access [Contact Profile](/ai/agents/analyze/contact-profiles) information for the current user. Select one of the following options: | | Selected Profile Fields | Text | This parameter appears when the **Inject selected Profile fields** option is enabled. Enter specific fields from the Contact Profile for targeted data use. Specify the field using the [Profile keys](/ai/agents/analyze/contact-profiles#profile-schema) format and press Enter to apply it. | | Short-Term Memory Injection | CognigyScript | Specify a static string or a dynamic value via CognigyScript to make available to the AI Agent in the current turn. | | Parameter | Type | Description | | -------------------------- | ------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Knowledge Injection | Selector | Use the Knowledge AI feature for the AI Agent. Select one of the following options: | | Use AI Agent Knowledge | Toggle | Appears when you select **When Required** or **Once for Each User Input**. Enable to use the Knowledge Store configured in the AI Agent. The Knowledge Store configured within the [AI Agent creation settings](/ai/agents/develop/manage-ai-agents#create-ai-agents) will be used. | | Use Job Knowledge | Toggle | Appears when you select **When Required** or **Once for Each User Input**. Enable this option to configure a specific Knowledge Store for this particular job, allowing the AI Agent to access job-specific data or resources. | | Job Knowledge Store | Selector | Appears when you select **When Required** or **Once for Each User Input** and **Use Job Knowledge** is enabled. Select a specific Knowledge Store for this AI Agent's job. | | Top K | Slider | Appears when you select **When Required** or **Once for Each User Input**. Specify how many knowledge chunks to return. Providing more results gives the AI Agent additional context but may increase noise and token usage. | | Source Tags | CognigyScript | Appears when you select **When Required** or **Once for Each User Input**. Tags refine the scope of your knowledge search, including only the most relevant sections of the knowledge base to improve accuracy. Before specifying tags, ensure they were provided during the creation of the Knowledge Sources. Add tags by entering each separately and pressing Enter. Max 5 tags. When multiple Source Tags are specified, the Search Extract Output Node defaults to the `AND` operator, meaning it only considers Sources that have all specified tags. To change this behavior, adjust the **Match Type for Source Tags** parameter. | | Match Type for Source Tags | Select | Appears when you select **When Required** or **Once for Each User Input**. Defines the operator for filtering Knowledge Sources by tags: | | Generate Search Prompt | Toggle | Appears when you select **Once for Each User Input**. Enabled by default. Generates a context-aware search prompt before executing the knowledge search. May increase cost and latency. By default, the prompt includes the last 7 conversation turns. This value can't be changed. | | Parameter | Type | Description | | --------------------------- | ------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | How to handle the result | Select | Determine how to handle the prompt result: | | Input Key to store Result | CognigyScript | Appears when **Store in Input** or **Stream to Output** is selected. The result is stored in `input.aiAgentOutput` by default. You can specify another value, but the **AI Agent Output** token will not work if the value is changed. | | Context Key to store Result | CognigyScript | Appears when **Store in Context** is selected. The result is stored in `context.aiAgentOutput` by default. You can specify another key. | | Stream Buffer Flush Tokens | Text Array | Appears when **Stream to Output** is selected. Defines tokens that trigger the stream buffer to flush to the output. Tokens can be punctuation marks or symbols, such as `\n`. | | Output result immediately | Toggle | Appears when **Store in Input** or **Store in Context** is selected. Allows immediate output of results without using the Say Node and AI Agent Output token. | | Store Copy in Input | Toggle | Appears when **Stream to Output** is selected. In addition to streaming the result, stores a copy in the Input object by specifying a value in the **Input Key to store Result** field. | | Parameter | Type | Description | | ------------------------- | ------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Voice Setting | Select | Configure the voice settings for the AI Agent Job. This parameter determines how the AI Agent selects the voice for text-to-speech (TTS) output. Select one of the following options: | | TTS Vendor | Dropdown | Select a TTS vendor from the list or add a custom one. Note: The AI Agent Node doesn't support **TTS Labels** to distinguish configurations from the same vendor. To use **TTS Labels**, add a [Set Session Config Node](/ai/agents/develop/node-reference/voice/voice-gateway/set-session-config) before the AI Agent Node in the Flow editor. | | Custom (Vendor) | CognigyScript | Appears when **Custom** is selected in **TTS Vendor**. Specify the [custom TTS Vendor](/voice-gateway/webapp/speech-services#add-custom-speech-vendors). For preinstalled providers, use lowercase, for example, `microsoft`, `google`, `aws`. For custom providers, use the name defined on the [Speech Service](/voice-gateway/webapp/speech-services) page in the Voice Gateway Self-Service Portal. | | TTS Language | Dropdown | Define the language of the AI Agent output. Ensure it aligns with the preferred language of the end user. | | Custom (Language) | CognigyScript | Appears when **Custom** is selected in **TTS Language**. Specify the output language. Format depends on the TTS vendor; check vendor documentation. Typical format: `de-DE`, `fr-FR`, `en-US`. | | TTS Voice | Dropdown | Define the voice for AI Agent output. Customize tone, gender, style, and regional specifics to align conversations with your brand and audience. | | Custom (Voice) | CognigyScript | Appears when **Custom** is selected in **TTS Voice**. Specify a custom voice, often required for region-specific voices. Format depends on **TTS Vendor** and typically follows `language-region-VoiceName`, for example, `de-DE-ConradNeural`, `en-US-JennyNeural`. | | TTS Label | CognigyScript | Alternative name for the TTS vendor, as specified in the [Voice Gateway Self-Service Portal](/voice-gateway/webapp/applications#add-additional-tts-and-stt-vendor). Use this when multiple speech services from the same vendor exist. | | Disable TTS Audio Caching | Toggle | Disables TTS audio caching. By default, the setting is deactivated. In this case, previously requested TTS audio results are stored in the AI Agent cache. When a new TTS request is made and the audio text has been previously requested, the AI Agent retrieves the cached result instead of sending another request to the TTS provider.
When the setting is activated, the AI Agent caches TTS results but doesn't use them. In this case, each request is directly sent to your speech provider.
Note that disabling caching can increase TTS costs. For detailed information, contact your speech provider. | | Parameter | Type | Description | | --------------- | -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Tool Choice | Selector | If supported by your LLM Model, determines how tools should be selected by the AI Agent: | | Use Strict Mode | Toggle | When enabled, strict mode (if supported by the LLM provider) ensures that arguments passed to a tool call precisely match the expected parameters. This helps prevent errors but may slightly delay responses, especially during the first call after making changes. | | Parameter | Type | Description | | -------------------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Process Images | Toggle | Enables the AI Agent to read and understand image attachments. Ensure that your LLM provider supports image processing (refer to your provider's documentation). Also verify that attachments are supported and activated in your Endpoint, such as Webchat. | | Images in Transcript | Selector | Configures how images older than the last turn are handled to reduce token usage: Limitations and token consumption depend on the LLM used. | | Parameter | Type | Description | | -------------------------- | -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | LLM | Selector | Select a model that supports the [AI Agent Node feature](/ai/agents/develop/gen-ai-and-llms/model-support-by-feature). The selected **Default** model is the one specified in **Settings > Generative AI Settings** of your Project. Choose the model you [added earlier](/ai/agents/overview#prerequisites) while configuring the Agentic AI feature. This model will manage your AI Agent. | | AI Agent Base Version | Selector | Select the base version of the AI Agent to use:When upgrading to a fixed version or switching to the latest, always test your AI Agent carefully to ensure compatibility. | | Timeout | Number | Define the maximum number of milliseconds to wait for a response from the LLM provider. | | Maximum Completion Tokens | Slider | Set the maximum number of tokens that can be used during a process to manage costs. If the limit is too low, the output may be incomplete. For example, setting 100 tokens roughly corresponds to 100 words, depending on language and tokenization. | | Temperature | Slider | Define the sampling temperature, ranging from 0 to 1. Higher values, for example, 0.8, make output more random; lower values, for example, 0.2, make it more focused and deterministic. | | Include Rich Media Context | Toggle | Controls whether the text from the [Textual Description](/ai/agents/develop/node-reference/basic/say#output-type) field in Say, Question, and Optional Questions Nodes is added to the AI Agent's prompt. This text provides AI Agents with additional information, improving their responses.

If you have filled in a **Textual Description** field in other Nodes, this text is added to the prompt as context for rich media, such as Text with Quick Replies. If the **Textual Description** field is empty, the button titles and alt text from the rich media are added to the prompt. By default, the **Include Rich Media Context** parameter is active. When this parameter is inactive, nothing related to the rich media is added to the prompt.

**Examples**: | | Parameter | Type | Description | | ------------------------------ | ------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Log to System Logs | Toggle | Log errors to the system logs. They can be viewed on the [Logs](/ai/agents/test/logs) page of your Project. This parameter is inactive by default. | | Store in Input | Toggle | Store errors in the Input object. | | Select Error Handling Approach | Select | Choose one of the Error Handling options: | | Select Flow | Select | Appears when **Go to Node** is selected. Choose a Flow from the available options. | | Select Node | Select | Appears when **Go to Node** is selected. Choose a Node from the available options. | | Error Message (optional) | CognigyScript | Add an optional message to the output if the AI Agent Node fails. | These options let you use parameters that aren't included in the AI Agent Node or overwrite set configurations. | Parameter | Type | Description | Example | | ---------------------- | ---- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------- | | Custom Options | JSON | Set custom parameters to the LLM configuration. You can set individual parameters as well as entire functions. These parameters customize the behavior of the model, such as adjusting `temperature`, `top_k`, or `presence_penalty`. This field overrides the parameters set in the AI Agent Node. To view the full list of available parameters for your model, refer to the LLM provider's API documentation, for example, [OpenAI](https://platform.openai.com/docs/api-reference/chat/create) or [Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-services/openai/). | `{ "model": "gpt-4o", "temperature": 0.7, "max_tokens": 4000 }` | | Custom Request Options | JSON | Set custom parameters to customize the request to the LLM provider. These parameters override the configurations set in this Node. For example, setting a `{ "stream": true }` parameter overrides the **Output result immediately** option. For more information, refer to the LLM provider's API documentation. | `{ "stream": true }`, `{ "headers": { "Authorization": "Bearer " } }` | **Forcing Model Versions** You can force the AI Agent Node to use a specific model version by including it in the Custom Options. This means that the AI Agent Node will use the specified version of the language model instead of the default or any other available versions. This allows for more control over the behavior of the AI Agent Node, ensuring it uses the desired model version for generating prompts or responses. You can use models from any LLM provider supported by Cognigy, including those not yet directly integrated. However, you can only replace a model with another from the same provider. Let's consider an example with Anthropic: You can force the AI Agent Node to use the model version `claude-opus-4-1-20250805`, despite the LLM resource defaulting to the `claude-opus-4-5-20251101` model: 1. [Create an Anthropic LLM resource](/ai/agents/develop/gen-ai-and-llms/providers/anthropic) for Claude, for example, `claude-opus-4-5-20251101`. 2. Create a Flow and add an AI Agent Node to it. 3. In the AI Agent Node, select the model `claude-opus-4-5-20251101` from the **Large Language Model** list. 4. In the **Custom Model Options** field, add `{ "model": "claude-opus-4-1-20250805" }` to force the use of the `claude-opus-4-1-20250805` model. 5. Click **Save Node**. The AI Agent Node now utilizes the `claude-opus-4-1-20250805` model. Below, you'll find documentation for supported models: * [Aleph Alpha Models](https://docs.aleph-alpha.com/) * [Anthropic Models](https://docs.anthropic.com/claude/docs/models-overview) * [Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models) * [OpenAI Models](https://platform.openai.com/docs/models) | Parameter | Type | Description | | ----------------------------- | ------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Log Job Execution | Toggle | Send a debug message with the current AI Agent Job configuration. The message appears in the Interaction Panel when debug mode is enabled. The parameter is active by default. | | Log Knowledge Results | Toggle | Send a debug message containing the result from a knowledge search. The message appears in the Interaction Panel when debug mode is enabled. The parameter is inactive by default. | | Show Token Count | Toggle | Send a debug message containing the input, output, and total token count. The message appears in the Interaction Panel when debug mode is enabled. Cognigy.AI uses the GPT-3 tokenizer algorithm, so actual token usage may vary depending on the model used. The parameter is inactive by default. | | Log System Prompt | Toggle | Send a debug message containing the system prompt. The message appears in the Interaction Panel when debug mode is enabled. The parameter is inactive by default. | | Log Tool Definitions | Toggle | Send a debug message containing information about the configured AI Agent tools. The message appears in the Interaction Panel when debug mode is enabled. The parameter is inactive by default. | | Log LLM Latency | Toggle | Send a debug message containing key latency metrics for the request to the model, including the time taken for the first output and the total time to complete the request. The message appears in the Interaction Panel when [debug mode](/ai/agents/test/interaction-panel/chat#debug-mode) is enabled. The parameter is inactive by default. | | Send request logs to Webhook | Toggle | Send the request sent to the LLM provider and the subsequent completion to a webhook service, including metadata, the request body, and custom logging data. With this parameter, you can use a webhook service to view detailed logs of the request to the LLM. The parameter is inactive by default. | | Webhook URL | CognigyScript | Enter the URL of the webhook service to send the request logs to. | | Custom Logging Data | CognigyScript | Enter custom data to send with the request to the webhook service. | | Condition for Webhook Logging | CognigyScript | Enter the condition for the webhook logging. | | Webhook Headers | Input fields | Enter the headers to send with the request to the webhook service. Use the **Key** and **Value** fields to enter a header. The **Value** field supports CognigyScript. After entering the header key, new empty **Key** and **Value** fields are automatically added, in case you need to add more headers. Alternatively, you can click **Show JSON Editor** and add input examples in the code field. | ### Child Nodes #### Tool Tools are child Nodes of AI Agent Nodes. They define the actions the AI Agent can take. If an AI Agent wants to execute the tool, the branch below the child Node is executed. At the end of a tool branch, it is advisable to use a [Resolve Tool Action](/ai/agents/develop/node-reference/ai/resolve-tool-action) Node to return to the AI Agent. Clicking the Tool Node lets you define a tool, set its parameters, and allows debugging by enabling detailed messages about the tool's execution. | Parameter | Type | Description | | ----------- | ------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------- | | Tool ID | CognigyScript | Provide a meaningful name as a Tool ID. This ID can contain only letters, numbers, underscores (`_`), or dashes (`-`). For example, `update_user-1`. | | Description | CognigyScript | Provide a detailed description of what the tool does, when it should be used, and its parameters. | Configure the parameters that the AI Agent will collect before the tool is called. You can switch between the Graphical and JSON editors. When editing the JSON, follow the [JSON Schema specification](https://json-schema.org). | Parameter | Type | Description | | --------------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Use Parameters | Toggle | Activate this toggle to add parameters in addition to the tool name and description. The AI Agent will collect all data it needs and call a Tool with these parameters filled as arguments. These values can be accessed directly in the `input.aiAgent.toolArgs` object. | | Name | Text | Specify the name of the parameter. The name should be clear and concise, and describe the purpose of the parameter. | | Type | Selector | Select a type of the parameter: | | Description | Text | Explain what the parameter means by providing a brief description of the parameter's usage. | | Enum (optional) | Enum | Define a set of values that the parameter can accept. The enum restricts the input to one of the specified values, ensuring only valid options are chosen. The enum is only available for string-type parameters in the Graphical editor. For other types, use the JSON editor. May not be supported by all LLM providers. | | Add Parameter | Button | Add a new parameter. | | Parameter | Type | Description | | ------------------------- | ------ | ----------------------------------------------------------------------------------------------------------------- | | Debug Message when called | Toggle | Enable the output of a debug message when the tool is called to provide detailed information about the tool call. | | Parameter | Type | Description | | --------- | ------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Condition | CognigyScript | The tool will be enabled only if the condition is evaluated as true. If false, the tool isn't part of the AI Agent's Tools within this execution. For example, when using the `unlock_account` tool, you can specify a condition like `context.accountStatus === "locked"`. This checks the value in the context, and if it is missing or different, the tool will not be enabled. | #### MCP Tool MCP Tool Nodes are child Nodes of AI Agent Nodes. The MCP Tool Nodes connect to a remote [MCP server](https://modelcontextprotocol.io/introduction) to load tools that the AI Agent can execute. If an AI Agent wants to execute one of the loaded tools, the branch below the MCP Tool Node is triggered. Clicking the MCP Tool Node lets you define the connection, filter loaded tools, and allows debugging by enabling detailed messages about the tool's execution. | Parameter | Type | Description | | ------------------ | ------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Name | CognigyScript | Provide a name for the MCP connection. This name helps you identify the source of the loaded tool. | | MCP Server SSE URL | CognigyScript | Provide the URL to an SSE (Server-Sent Events) endpoint from a remote [MCP server](https://modelcontextprotocol.io/introduction). Ensure that you connect only to trusted MCP servers. | | Timeout | Slider | Set the timeout time for the MCP connection in seconds. | | Parameter | Type | Description | | ------------------- | -------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Authentication Type | Selector | The authentication type to use for the MCP server connection. Select one of the following options: If you want to use a different authentication method, such as an API key, you can add it as a custom header in **Custom Headers** of the **Advanced** section. | | OAuth2 Parameters | Selector | Opens the fields required to configure OAuth 2.0 authentication. These fields allow the AI Agent to securely request and use access tokens when communicating with the MCP server. Configure the following fields: | | Parameter | Type | Description | | --------------------- | ------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Debug Loaded Tools | Toggle | Enable this parameter to display a debug message listing all tools loaded from the MCP server. The debug message also includes tools filtered out in the Advanced section. This parameter shows whether tools were loaded from the cache or directly from the MCP server. | | Debug with Parameters | Toggle | Enable this parameter to include the Tool Parameters in the debug message. | | Debug calling Tool | Toggle | Enable the output of a debug message when the tool is called to provide detailed information about the tool call. | | Parameter | Type | Description | | -------------- | ------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Cache Tools | Toggle | Disables caching of loaded tools while developing. Ensure that caching is enabled in production for performance reasons. The caching time is 10 minutes. In debug mode, you can verify whether the cache was used. To do this, make sure **Debug Loaded Tools** is enabled. For more information, see the [Debug Settings](#debug-settings) section. | | Condition | CognigyScript | Sets the condition under which the tool will be activated. If the condition is evaluated as false, the tool isn't part of the AI Agent's Tools during execution. For example, when using the `unlock_account` tool, you can specify a condition like `context.accountStatus === "locked"`. This checks the value in the context, and if it is missing or different, the tool will not be enabled. | | Tool Filter | Select | Controls if tools should be excluded from execution. You can select one of the following options: | | Blacklist | CognigyScript | This parameter appears if you select **Blacklist** in **Tool Filter**. Specify the tools that should be blocked from execution. Specify only one tool per field. | | Whitelist | CognigyScript | This parameter appears if you select **Whitelist** in **Tool Filter**. Specify the tools you want to allow for execution. Specify only one tool per field. | | Custom Headers | - | Sets custom authentication headers to send with the request to the MCP server. Use the **Key** and **Value** fields to enter a header. The **Value** field supports CognigyScript. After entering the header key, new empty **Key** and **Value** fields are automatically added, in case you need to add more headers. Alternatively, you can click **Show JSON Editor** and enter the headers in the code field. | #### Call MCP Tool In the Flow editor, when you add an MCP Tool Node, a Call MCP Tool Node is automatically created below it. These two Nodes work together to define and execute the chosen tool. The Call MCP Tool Node sets the actual execution point of the chosen tool. This way, you can verify or modify the tool call arguments in the `input.aiAgent.toolArgs` object, or add a Say Node before the tool call. When the Call MCP Tool Node is executed, the tool call is sent to the remote MCP server, where the Tool is executed remotely with any arguments set by the AI Agent. To return the tool result to the AI Agent, the **Resolve Immediately** setting can be enabled to send the full result returned from the remote MCP server to the AI Agent. As an alternative, use a [Resolve Tool Action](/ai/agents/develop/node-reference/ai/resolve-tool-action) Node to return a specific result to the AI Agent. | Parameter | Type | Description | | ------------------- | ------ | ----------------------------------------------------------------------------------------------------- | | Resolve Immediately | Toggle | Enable this parameter to immediately resolve the tool action with the full result as the tool answer. | | Parameter | Type | Description | | --------------------------- | ------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | How to handle the result | Select | Determine how to handle the MCP tool call result: | | Input Key to store Result | CognigyScript | The parameter appears when **Store in Input** is selected. The result is stored in the `input.aiAgent.toolResult` object by default. You can specify another value, but the **MCP Tool Result** Token won't work if the value is changed. | | Context Key to store Result | CognigyScript | The parameter appears when **Store in Context** is selected. The result is stored in the `context.aiAgent.toolResult` object by default. | | Parameter | Type | Description | | ----------------- | ------ | --------------------------------------------------------------------------------------- | | Debug Tool Result | Toggle | Enable the output of a debug message with the tool call result after a successful call. | #### Knowledge Tool The Knowledge Tool Node is a child Node of the AI Agent Node. It allows the AI Agent to directly access [Knowledge Stores](/ai/agents/develop/knowledge-ai/knowledge-store) to provide context-aware responses. In the Knowledge Tool Node, you can select the [Knowledge Store](/ai/agents/develop/knowledge-ai/knowledge-store) to search, [Source Tags](/ai/agents/develop/knowledge-ai/knowledge-source/knowledge-source-tags) to refine the search, and allows for detailed debug messages about the tool's execution. | Parameter | Type | Description | | --------------- | ------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Knowledge Store | Selector | Select a Knowledge Store. | | Tool ID | CognigyScript | Enter a name as a tool ID. This ID can contain only letters, numbers, underscores (`_`), or dashes (`-`). If you use more than one Knowledge tool, the tool ID provides context to trigger the correct Knowledge tool. In this case, enter a clear tool ID for each Knowledge tool, for example, `search_appliances` | | Description | CognigyScript | Enter instructions to guide the AI Agent to call the Knowledge tool. The description field provides context to trigger the Knowledge tool. If you want to use more than one Knowledge tool, enter clear instructions for the cases when each Knowledge tool should be used. For example, `Find the answer to prompts or questions about appliances by searching the attached data sources. Use this tool when a customer asks about appliance items such as washing machines, dryers, and other household appliances. Focus exclusively on a knowledge search and does not execute tasks like small talk, calculations, or script running.` | | Parameter | Type | Description | | ------------------------- | ------ | ----------------------------------------------------------------------------------------------------------------- | | Debug Message when called | Toggle | Enable the output of a debug message when the tool is called to provide detailed information about the tool call. | | Parameter | Type | Description | | --------------------------- | ------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Top K | Slider | Set how many Knowledge Chunks to return. Providing more results gives the AI Agent additional context, but it also increases noise and token usage. | | Store Location | Selector | Select whether and where to store the knowledge search results. Select one of the following options: | | Input Key to store result | CognigyScript | Appears when **Store Location** is set to **Input**. The property in the Input object where the result is stored. For example, `input.knowledgeSearch`. | | Context Key to store result | CognigyScript | Appears when **Store Location** is set to **Context**. The property in the Context object where the result is stored. For example, `context.knowledgeSearch`. | | Source Tags | CognigyScript | Enter [Knowledge Source Tags](/ai/agents/develop/knowledge-ai/knowledge-source/knowledge-source-tags) to refine the scope of your knowledge search, including only the most relevant Knowledge Chunks in the Knowledge Store. Before entering tags, ensure they are included in the Knowledge Sources. Add tags by entering each separately and pressing Enter. Max 5 tags. When multiple Source Tags are specified, the Search Extract Output Node defaults to the `AND` operator, meaning it only considers Sources that have all specified tags. To change this behavior, adjust the **Match Type for Source Tags** parameter. | | Match type for Source Tags | Selector | The operator to filter Knowledge Sources by Source Tags. Select one of the following options: | | Condition | CognigyScript | The Knowledge tool is activated only if the condition is evaluated as true. If false, the tool isn't included in the current execution. For example, when using the Knowledge tool, you can enter a condition such as `context.productCategory === "appliances"`. This checks the value in the context, and if it is missing or different, the tool isn't activated. | #### Send Email Tool The Send Email tool lets your AI Agent send emails directly to users. The Send Email tool uses the same configuration and restrictions as the [Email Notification Node](/ai/agents/develop/node-reference/data/email-notification) but adds more flexibility. While the Email Notification Node sends emails at a fixed step in a Flow, the Send Email tool allows the AI Agent to send emails dynamically, based on user input, conversation context, or instructions. This tool makes automation more flexible and minimizes extra Flow steps. | Parameter | Type | Description | | ---------------------------- | ------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- | | Tool ID | CognigyScript | Provide a meaningful name as a tool ID. This ID can contain only letters, numbers, underscores (`_`), or dashes (`-`). The default name is `send_email`. | | Description | CognigyScript | Provide a detailed description of what the tool should do. The default description is `Create and send a new email message.` | | Recipient TO Email Addresses | CognigyScript | A comma-separated list of email addresses to which the email will be sent. | | Parameter | Type | Description | | ------------------------- | ------ | ----------------------------------------------------------------------------------------------------------------- | | Debug Message when called | Toggle | Enable the output of a debug message when the tool is called to provide detailed information about the tool call. | | Parameter | Type | Description | | --------- | ------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Condition | CognigyScript | The tool will be enabled only if the condition is evaluated as true. If false, the tool isn't part of the AI Agent's Tools within this execution. For example, when using the `unlock_account` tool, you can specify a condition like `context.accountStatus === "locked"`. This checks the value in the context, and if it is missing or different, the tool will not be enabled. | #### Handover to AI Agent Tool The Handover to AI Agent tool lets you transfer a conversation to another AI Agent in the same or a different Flow. This approach ensures the conversation keeps its context, different AI Agents can handle specific tasks, and multi-step conversations run smoothly across Flows. | Parameter | Type | Description | | ----------- | ------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Tool ID | CognigyScript | Provide a meaningful name as a tool ID. This ID can contain only letters, numbers, underscores (`_`), or dashes (`-`). The default name is `handover_to_ai_agent`. | | Description | CognigyScript | Describe what the receiving AI Agent should do. For example: `Handle product recommendations`, `Perform technical troubleshooting`, or `Assist with billing questions`. Be specific so the handover rules clearly indicate when this AI Agent should take over. | | Select Flow | Selector | Select the target Flow to hand over to. By default, all Flows in the Project are displayed in the list. The selected Flow must contain an AI Agent Node. | | Select Node | Selector | Select the AI Agent Node to hand over to. | | Parameter | Type | Description | | ------------------------- | ------ | ----------------------------------------------------------------------------------------------------------------- | | Debug Message when called | Toggle | Enable the output of a debug message when the tool is called to provide detailed information about the tool call. | | Parameter | Type | Description | | --------- | ------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Condition | CognigyScript | The tool will be enabled only if the condition is evaluated as true. If false, the tool isn't part of the AI Agent's Tools within this execution. For example, when using the `unlock_account` tool, you can specify a condition like `context.accountStatus === "locked"`. This checks the value in the context, and if it is missing or different, the tool will not be enabled. | #### Handover to Human Agent Tool The Handover to Human Agent tool lets you transfer a conversation to a human agent through handover providers. This tool allows your AI Agents to refer complex tasks to a human agent if they can't address the user's request. | Parameter | Type | Description | | -------------------------------- | ------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Tool ID | CognigyScript | Provide a meaningful name as a tool ID. This ID can contain only letters, numbers, underscores (`_`), or dashes (`-`). The default name is `handover_to_human_agent`. | | Description | CognigyScript | Describe the situation when the AI Agent should refer to a human agent. For example: `Use this tool if the user explicitly asks for a human.`, or `Use this tool if you fail to answer the user's question three times.`. Be specific so the handover rules clearly indicate when the conversation should be handed over to the receiving human agent. | | Handover Provider | Selector | Select the handover provider from the list. The **Legacy** option is selected by default, meaning the node configuration points to the settings in **Deploy > Endpoints > Handover Settings**. To select a provider from the list, you need to either migrate your settings to the [Handover Providers](/ai/escalate/migration) interface or create this handover provider from scratch. | | Handover Accepted Message | CognigyScript | The message to be outputted when the handover is requested. | | Repeat Handover Accepted Message | Toggle | Enable to repeatedly output the Handover Accepted Message if the user sends a message while waiting in the queue for an agent. | | Parameter | Description | | ------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Live Agent Inbox Id | Enter the Inbox ID that you obtained in the [previous step](/ai/escalate/handover-reference/live-agent). | | Skills | Enter a list of skills that should be used to filter the available agents. For example, `technical support, billing`. | | Languages | Enter a list of languages that should be used to filter the available agents. For example, `english, spanish`. | | Priority | Select a priority for the conversation from the list. For example, `Urgent`. | | Get Queue Position | Enable the system to retrieve the end user's current queue position. This parameter is inactive by default. | | Update Interval | Specify the interval, in seconds, for how often to receive updates on the queue status. This parameter appears if **Get Queue Position** is selected. | | Get Estimated Wait Time | Enable the retrieval of the estimated wait time for the end user. This parameter is inactive by default. | | Wait Time Update Interval | Set the interval, in seconds, for how often to receive updates on estimated wait time. This parameter appears if **Get Estimated Wait Time** is selected. | | Alternative Update | The alternative update options when certain conditions are met. This parameter is inactive by default. | | Maximum Queue Position | Set the threshold for the maximum queue position. If this threshold is reached, the alternative text is sent. This parameter appears if **Alternative Update** is selected. | | Maximum Estimated Wait Time | Define the maximum estimated wait time in milliseconds. If this duration is exceeded, the alternative text is sent. This parameter appears if **Alternative Update** is selected. | | Alternative Text | The message to be sent when either the maximum queue position or maximum wait time is reached. This parameter appears if **Alternative Update** is selected. | | Enable User Connects Message | Notify human agents when an end user reconnects to the chat. The parameter is enabled by default. When the parameter is enabled, the message `User joined the conversation` appears in the chat as soon as the end user returns to the chat tab by clicking the **←** (back arrow) at the top bar in the browser, after having opened a new URL on the same tab as the chat. | | Enable User Disconnects Message | Notify human agents when an end user disconnects from the chat. The parameter is enabled by default. When the parameter is enabled, the message `User left the conversation` is sent as soon as the end user closes the tab with the chat or switches to a new URL address within the current tab. | For more information, read the [Live Agent Handover Setup](/live-agent/getting-started/live-agent-setup/live-agent-setup-handover-flow) and [Real-Time Queue Notifications](/live-agent/conversation/conversation-queue/real-time-queue-notifications) documentation. | Parameter | Description | | ----------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Chatwoot Inbox Id | Enter the Chatwoot Inbox ID. You can find the Inbox ID in your Chatwoot URL. For example, `https://app.chatwoot.com/app/account/6607/inbox/5446`, where the Inbox ID is `5446`. For more information, read the [Chatwoot handover provider](/ai/escalate/handover-reference/chatwoot) documentation. | | Parameter | Description | | -------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Send Transcript as first message | Activate this parameter to allow Salesforce to receive the conversation transcript as the first message. This setting is turned off by default. | | Button ID | Enter the ID of the Button you created in the Salesforce installation. This setting will override the default Button ID that you specified in the Endpoint configuration. You can use different Button IDs for individual Handover to Agent Nodes. | | Pre-chat Entities | Enter the pre-chat entities. For more information, read the [Salesforce Handover](/ai/escalate/handover-reference/salesforce) documentation. | | Pre-chat Details | Enter the pre-chat details. For more information, read the [Salesforce Handover](/ai/escalate/handover-reference/salesforce) documentation. | | Parameter | Description | | -------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Send Transcript as first message | Activate this parameter to allow NiCE CXone to receive the conversation transcript as the first message when the handover begins. This setting is turned on by default. | | Parameter | Description | | ------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Language | Specify a language for the conversation. For example, `english`, `spanish`, `german`. | | Skills | Define skills for the conversation. For example, `escalation`. | | Priority | Set the priority for the conversation. For example, `1`.
If a priority is set, it triggers a flow in Genesys to prioritize or de-prioritize the conversation within the queue.
Note that this functionality requires the appropriate flow to be set up in Genesys. | | Enable User Connects Message | Notify human agents when an end user reconnects to the chat. The parameter is enabled by default. When the parameter is enabled, the message `User joined the conversation` appears in the chat as soon as the end user returns to the chat tab by clicking the **←** (back arrow) at the top bar in the browser, after having opened a new URL on the same tab as the chat. | | Enable User Disconnects Message | Notify human agents when an end user disconnects from the chat. The parameter is enabled by default. When the parameter is enabled, the message `User left the conversation` is sent as soon as the end user closes the tab with the chat or switches to a new URL address within the current tab. | | Custom Attributes | Add custom attributes in the `Key: Value` format, which allows you to include additional information. | Example for the **Custom Attributes** parameter: ```json theme={null} { "section": "section A", "region": "Europe" } ``` For more information, read the [Genesys Cloud Guest Chat](/ai/escalate/handover-reference/genesys-cloud-guest-chat#prerequisites) and [Genesys Cloud Open Messaging](/ai/escalate/handover-reference/genesys-cloud-open-messaging) documentation. | Parameter | Description | | ------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | 8x8 Channel Id | Specify the channel ID that you created during the 8x8 configuration.
You can find this ID in the 8x8 admin console. Navigate to **Channels > Chat API**. In the channel list, find the channel that you created. Copy the **ID** from the channel row. | | 8x8 Queue Id | Specify the header value required for authenticating API calls to the 8x8 system.
You can find this ID in the 8x8 admin console. Navigate to **Channels > Chat API**. In the channel list, find the channel that you created. Copy the **Queue ID** from the channel row. | | 8x8 JSON properties | Extend 8x8 properties with custom JSON. | For more information, read the [8x8 Handover Setup](/ai/escalate/handover-reference/8x8) documentation. | Parameter | Type | Description | | ------------------------------- | ------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Additional Category Ids | CognigyScript | IDs to be passed to the RingCentral Engage handover provider. | | Enable User Connects Message | Toggle | Notify human agents when an end user reconnects to the chat. The parameter is enabled by default. When the parameter is enabled, the message `User joined the conversation` appears in the chat as soon as the end user returns to the chat tab by clicking the **←** (back arrow) at the top bar in the browser, after having opened a new URL on the same tab as the chat. | | Enable User Disconnects Message | Toggle | Notify human agents when an end user disconnects from the chat. The parameter is enabled by default. When the parameter is enabled, the message `User left the conversation` is sent as soon as the end user closes the tab with the chat or switches to a new URL address within the current tab. | For more information, read the [RingCentral Engage Integration](/ai/escalate/handover-reference/ring-central-engage) documentation. | Parameter | Type | Description | | ------------------ | ------------- | ---------------------------------------------------------------------------------------------------- | | Cancel Intent | CognigyScript | The Intent the user has to trigger to cancel the Handover request. | | Cancel Button Text | CognigyScript | The text for a quick reply button that cancels the handover request when the user clicks the button. | | Parameter | Type | Description | | ----------------------------------- | ------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Flow Continuation | List | | | Send resolve event to Virtual Agent | Toggle | Sending an event when the AI Agent resolves a conversation. | | Parameter | Type | Description | | ----------------- | ------ | ------------------------------------------------------- | | Send Queue Event | Toggle | Sends an event to the Flow once the handover is queued. | | Send Active Event | Toggle | Sends an event to the Flow once the handover is active. | | Parameter | Type | Description | | ------------------------- | ------ | ----------------------------------------------------------------------------------------------------------------- | | Debug Message when called | Toggle | Enable the output of a debug message when the tool is called to provide detailed information about the tool call. | | Parameter | Type | Description | | --------- | ------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Condition | CognigyScript | The tool will be enabled only if the condition is evaluated as true. If false, the tool isn't part of the AI Agent's Tools within this execution. For example, when using the `unlock_account` tool, you can specify a condition like `context.accountStatus === "locked"`. This checks the value in the context, and if it is missing or different, the tool will not be enabled. | #### Execute Workflow Tool The Execute Workflow tool lets the AI Agent execute another Flow. After the target Flow executes, the conversation returns to the AI Agent. The target Flow inherits the [Context object](/ai/agents/develop/ai-agent-memory/context) from the AI Agent. If the Context object is changed during the target Flow execution, these changes are also available to the AI Agent. | Parameter | Description | | ----------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Tool ID | Enter a meaningful name as a tool ID. This ID can contain only letters, numbers, underscores (`_`), or dashes (`-`). The default name is `execute_workflow`. | | Description | Describe when to trigger the AI Agent to execute the target Flow. For example, if you have a specific Flow for dealing with package returns, enter: `Use this tool if the user explicitly asks to return a package.`. Be specific so the AI Agent only executes the target Flow when necessary. | | Target Flow | Select the target Flow that the AI Agent executes when this tool is called. Click target-flow to open the target Flow. | | Select Node | Select the target Node that the AI Agent executes when the target Flow is called. You must set the Node you want to select as an Entrypoint with the [Set Entrypoint](/ai/agents/develop/nodes/overview#set-nodes-as-entrypoints) setting before you can select it. | | Parameter | Type | Description | | ------------------------- | ------ | ------------------------------------------------------------------------------------------------------------------- | | Debug Message when called | Toggle | Activate the output of a debug message when the tool is called to provide detailed information about the tool call. | | Parameter | Type | Description | | -------------- | ------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Parse Intents | Toggle | Sets whether Intents should be parsed in the target Flow. This parameter is activated by default.

If this parameter is enabled, Cognigy NLU reparses the Intents in the target Flow based on `text` in the [Input object](/ai/agents/develop/ai-agent-memory/input#accessing-input-properties) and generates Intent scores using the Intents in the target Flow instead of the ones in the Flow the AI Agent is currently in. | | Parse Slots | Toggle | Sets whether Slots should be parsed in the target Flow. This parameter is activated by default.

If this parameter is enabled, Cognigy NLU reparses the Slots in the target Flow based on `text` in the [Input object](/ai/agents/develop/ai-agent-memory/input#accessing-input-properties) and generates Slot scores using the Slots in the target Flow instead of the ones in the Flow the AI Agent is currently in. | | Absorb Context | Toggle | Sets whether the [default Context object](/ai/agents/develop/ai-agent-memory/context#default-context) of the target Flow is used in the context of the Flow the AI Agent is currently in.

If the default Context of the target Flow has a value, it is copied into the Context object of the AI Agent as soon as the target Flow is executed. | ## Examples ### Tool In this example, the `unlock_account` tool unlocks a user account by providing the email and specifying the reason for the unlocking. Parameter configuration in JSON: ```json theme={null} { "type": "object", "properties": { "email": { "type": "string", "description": "User's login email for their account." } }, "required": ["email"], "additionalProperties": false } ``` where: * `type` — the type for a tool parameter schema, which must always be `object`. * `properties` — defines the parameters for the tool configuration: * `email` — a required tool parameter for unlocking the account. * `type` — defines the data type for the tool parameter. * `description` — a brief explanation of what the property represents. * `required` — lists `email` as a required parameter, ensuring that this value is always provided when the tool is called. * `additionalProperties` — ensures that the input contains only the `email` tool parameter, and no others are allowed. ### MCP Tool and Call MCP Tool #### Use Zapier's Remote MCP server You can create a custom MCP server with personalized tools by using one of the [provided SDKs](https://github.com/modelcontextprotocol). For a quicker setup, you can use a third-party provider. For example, [Zapier](https://zapier.com/) allows you to [configure your MCP server](https://actions.zapier.com/settings/mcp/), which can be connected to multiple application APIs. To use Zapier as a remote MCP server, follow these steps: 1. Log in to your Zapier account, go to the [MCP settings](https://actions.zapier.com/settings/mcp/) page, and configure your MCP server. 2. Copy the SSE URL and paste it into the **MCP Server SSE URL** field of your MCP Tool Node. 3. In the Zapier MCP settings, create an action to connect to various APIs. For example, you can create a Zapier action to automatically generate a Google Doc. Once the setup is complete, the configured MCP Actions will be loaded when the AI Agent is executed. You will see the following debug message in the Interaction Panel, indicating the result of the tool call after a successful execution: ```txt theme={null} AI Agent: MCP Tool Fetched tools from MCP Tool "zapier" - google_docs_create_document_from_: Create a new document from text. Also supports limited HTML. Parameters: - title (string): Document Name - file (string): Document Content ``` ### Knowledge Tool In this example, you have two Knowledge tools to search two different Knowledge Stores. Each Knowledge Store refers to a different product category, in this example, appliances and furniture. To guide the AI Agent to use the correct Knowledge tool, enter a clear tool ID and description: * Knowledge Tool 1: * Tool ID: `search_appliances` * Description: `Find the answer to prompts or questions about appliances by searching the attached data sources. Use this tool when a customer asks about appliance items such as washing machines, dryers, and other household appliances. Focus exclusively on a knowledge search and does not execute tasks like small talk, calculations, or script running.` * Knowledge Tool 2: * Tool ID: `search_furniture` * Description: `Find the answer to prompts or questions about furniture by searching the attached data sources. Use this tool when a customer asks about furniture items such as sofas, tables, and other items. Focus exclusively on a knowledge search and does not execute tasks like small talk, calculations, or script running.` ## Get AI Agent Jobs and Tools via API You can retrieve all job configurations and associated tools for a specific AI Agent via the Cognigy.AI API [`GET /v2.0/aiagents/{aiAgentId}/jobs`](https://api-trial.cognigy.ai/openapi#get-/v2.0/aiagents/-aiAgentId-/jobs) request. The response includes each job's configuration details and a list of available tools. ## More Information * [AI Agent Handover](/ai/agents/develop/node-reference/ai/ai-agent-handover) * [Resolve Tool Action](/ai/agents/develop/node-reference/ai/resolve-tool-action) * [Add Memories](/ai/agents/develop/node-reference/analytics/add-memory) * [Agentic AI](/ai/agents/overview)