# How to integrate Airtable MCP with Autogen ```json { "title": "How to integrate Airtable MCP with Autogen", "toolkit": "Airtable", "toolkit_slug": "airtable", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/airtable/framework/autogen", "markdown_url": "https://composio.dev/toolkits/airtable/framework/autogen.md", "updated_at": "2026-05-12T10:00:41.159Z" } ``` ## Introduction This guide walks you through connecting Airtable to AutoGen using the Composio tool router. By the end, you'll have a working Airtable agent that can add new contacts from a signup list, create a project tracking table in workspace, delete outdated records from clients table through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Airtable account through Composio's Airtable MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Airtable with - [ChatGPT](https://composio.dev/toolkits/airtable/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/airtable/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/airtable/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/airtable/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/airtable/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/airtable/framework/codex) - [Cursor](https://composio.dev/toolkits/airtable/framework/cursor) - [VS Code](https://composio.dev/toolkits/airtable/framework/vscode) - [OpenCode](https://composio.dev/toolkits/airtable/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/airtable/framework/openclaw) - [Hermes](https://composio.dev/toolkits/airtable/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/airtable/framework/cli) - [Google ADK](https://composio.dev/toolkits/airtable/framework/google-adk) - [LangChain](https://composio.dev/toolkits/airtable/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/airtable/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/airtable/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/airtable/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/airtable/framework/crew-ai) ## TL;DR Here's what you'll learn: - Get and set up your OpenAI and Composio API keys - Install the required dependencies for Autogen and Composio - Initialize Composio and create a Tool Router session for Airtable - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Airtable tools - Run a live chat loop where you ask the agent to perform Airtable operations ## What is AutoGen? Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows. Key features include: - Multi-Agent Systems: Build collaborative agent workflows - MCP Workbench: Native support for Model Context Protocol tools - Streaming HTTP: Connect to external services through streamable HTTP - AssistantAgent: Pre-built agent class for tool-using assistants ## What is the Airtable MCP server, and what's possible with it? The Airtable MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Airtable account. It provides structured and secure access to your Airtable bases and tables, so your agent can create records, update fields, manage tables, retrieve schemas, and automate project tracking on your behalf. - Seamless record creation and management: Easily instruct your agent to add new records, create multiple entries at once, or delete outdated information across any Airtable table. - Intuitive table and field customization: Ask your agent to design new tables, add or modify fields, and tailor the structure of your bases for evolving projects and workflows. - Efficient schema discovery: Let your agent fetch detailed schema information, including fields and configurations, to power data-driven automation and analysis. - Collaborative commenting: Have your agent add or remove comments on specific records, making team collaboration and discussion much smoother from anywhere. - Bulk operations for productivity: Enable your agent to perform batch actions like creating or deleting multiple records in one go, saving you time on repetitive data management tasks. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `AIRTABLE_CREATE_BASE` | Create base | Creates a new Airtable base with specified tables and fields within a workspace. | | `AIRTABLE_CREATE_COMMENT` | Create Comment | Tool to create a comment on a specific Airtable record. Use when adding comments to records, mentioning collaborators using @[userId] syntax, or creating threaded comment replies. Supports optional parentCommentId for threaded conversations. | | `AIRTABLE_CREATE_FIELD` | Create Field | Creates a new field within a specified table in an Airtable base. | | `AIRTABLE_CREATE_RECORD_FROM_NATURAL_LANGUAGE` | Create Record From Natural Language | Creates a new record in an Airtable table from a natural language description. Fetches the table schema, uses an LLM to generate the correct field payload, and creates the record with typecast enabled for automatic type conversion. | | `AIRTABLE_CREATE_RECORDS` | Create records | Tool to create multiple records (up to 10) in a specified Airtable table. Use when you need to add new rows to a table with field values. Rate limit: 5 requests per second per base. | | `AIRTABLE_CREATE_TABLE` | Create table | Creates a new table within a specified existing Airtable base, allowing definition of its name, description, and field structure. | | `AIRTABLE_DELETE_COMMENT` | Delete Comment | Tool to delete a comment from a record in an Airtable table. Use when you need to remove an existing comment. Non-admin users can only delete their own comments; Enterprise Admins can delete any comment. | | `AIRTABLE_DELETE_MULTIPLE_RECORDS` | Delete multiple records | Tool to delete up to 10 specified records from a table within an Airtable base. Use when you need to remove multiple records in a single operation. | | `AIRTABLE_DELETE_RECORD` | Delete Record | Permanently deletes a specific record from an existing table within an existing Airtable base. | | `AIRTABLE_GET_BASE_SCHEMA` | Get Base Schema | Retrieves the detailed schema for a specified Airtable base, including its tables, fields, field types, and configurations, using the `baseId`. | | `AIRTABLE_GET_RECORD` | Get Record | Retrieves a specific record from an Airtable table by its record ID. Requires a known, valid record ID obtained from listing records or another API call - this tool cannot search or list records. Use the list records tool to find record IDs. Empty field values are not returned in the response. | | `AIRTABLE_GET_USER_INFO` | Get user information | Retrieves information, such as ID and permission scopes, for the currently authenticated Airtable user from the `/meta/whoami` endpoint. | | `AIRTABLE_LIST_BASES` | List bases | Retrieves all Airtable bases accessible to the authenticated user, which may include an 'offset' for pagination. | | `AIRTABLE_LIST_COMMENTS` | List Comments | Tool to list comments on a specific Airtable record. Use when retrieving comments for a record, with optional pagination support for large comment threads. | | `AIRTABLE_LIST_RECORDS` | List records | Tool to list records from an Airtable table with filtering, sorting, and pagination. Use when you need to retrieve multiple records from a table with optional query parameters. | | `AIRTABLE_UPDATE_COMMENT` | Update Comment | Tool to update an existing comment on a specific Airtable record. Use when modifying comment text or updating user mentions using @[userId] syntax. API users can only update comments they have created. | | `AIRTABLE_UPDATE_FIELD` | Update Field | Updates a field's name or description in an Airtable table. Use this action to modify field metadata without changing the field's type or options. At least one of 'name' or 'description' must be provided. | | `AIRTABLE_UPDATE_MULTIPLE_RECORDS` | Update multiple records | Tool to update up to 10 records in an Airtable table with selective field modifications. Use when you need to modify multiple existing records or perform upsert operations. Updates are not performed atomically. | | `AIRTABLE_UPDATE_MULTIPLE_RECORDS_PUT` | Update multiple records (PUT) | Tool to destructively update multiple records in Airtable using PUT, clearing unspecified fields. Use when you need to fully replace record data or perform upsert operations. Supports up to 10 records per request. | | `AIRTABLE_UPDATE_RECORD` | Update record | Modifies specified fields of an existing record in an Airtable base and table; the base, table, and record must exist. | | `AIRTABLE_UPDATE_RECORD_PUT` | Update record (PUT) | Updates an existing record in an Airtable base using PUT method. Use when you want to replace all field values, clearing any unspecified fields. For partial updates that preserve unspecified fields, use the PATCH-based update action instead. | | `AIRTABLE_UPDATE_TABLE` | Update Table | Updates the name, description, and/or date dependency settings of a table in Airtable. Use this action to modify table metadata without changing the table's fields or views. At least one of 'name', 'description', or 'dateDependencySettings' must be provided. | | `AIRTABLE_UPLOAD_ATTACHMENT` | Upload attachment | Uploads a file attachment to a specified field in an Airtable record. Use when you need to add a file to an attachment field. The file must be provided as a base64-encoded string. | ## Supported Triggers | Trigger slug | Name | Description | |---|---|---| | `AIRTABLE_BASE_METADATA_CHANGED_TRIGGER` | Base Metadata Changed | Triggers when an existing Airtable base changes its name or permission level. | | `AIRTABLE_BASE_SCHEMA_CHANGED_TRIGGER` | Base Schema Changed | Triggers when tables, fields, or views change in an Airtable base. | | `AIRTABLE_USER_PROFILE_CHANGED_TRIGGER` | User Profile Changed | Triggers when the connected Airtable user's profile information changes. | | `AIRTABLE_VIEW_CREATED_TRIGGER` | View Created | Triggers when a new view is created in an Airtable base. | | `AIRTABLE_VIEW_DELETED_TRIGGER` | View Deleted | Triggers when a previously known Airtable view is deleted. | | `AIRTABLE_VIEW_METADATA_CHANGED_TRIGGER` | View Metadata Changed | Triggers when an Airtable view changes its name or type. | ## Creating MCP Server - Stand-alone vs Composio SDK The Airtable MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Airtable. Instead of manually wiring Airtable APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely. With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster. ## Step-by-step Guide ### 1. Prerequisites You will need: - A Composio API key - An OpenAI API key (used by Autogen's OpenAIChatCompletionClient) - A Airtable account you can connect to Composio - Some basic familiarity with Autogen and Python async ### 1. Getting API Keys for OpenAI and Composio OpenAI API Key - Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider. - Keep the API key safe. Composio API Key - Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install dependencies Install Composio, Autogen extensions, and dotenv. What's happening: - composio connects your agent to Airtable via MCP - autogen-agentchat provides the AssistantAgent class - autogen-ext-openai provides the OpenAI model client - autogen-ext-tools provides MCP workbench support ```bash pip install composio python-dotenv pip install autogen-agentchat autogen-ext-openai autogen-ext-tools ``` ### 3. Set up environment variables Create a .env file in your project folder. What's happening: - COMPOSIO_API_KEY is required to talk to Composio - OPENAI_API_KEY is used by Autogen's OpenAI client - USER_ID is how Composio identifies which user's Airtable connections to use ```bash COMPOSIO_API_KEY=your-composio-api-key OPENAI_API_KEY=your-openai-api-key USER_ID=your-user-identifier@example.com ``` ### 4. Import dependencies and create Tool Router session What's happening: - load_dotenv() reads your .env file - Composio(api_key=...) initializes the SDK - create(...) creates a Tool Router session that exposes Airtable tools - session.mcp.url is the MCP endpoint that Autogen will connect to ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from autogen_agentchat.agents import AssistantAgent from autogen_ext.models.openai import OpenAIChatCompletionClient from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams load_dotenv() async def main(): # Initialize Composio and create a Airtable session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["airtable"] ) url = session.mcp.url ``` ### 5. Configure MCP parameters for Autogen Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for. What's happening: - url points to the Tool Router MCP endpoint from Composio - timeout is the HTTP timeout for requests - sse_read_timeout controls how long to wait when streaming responses - terminate_on_close=True cleans up the MCP server process when the workbench is closed ```python # Configure MCP server parameters for Streamable HTTP server_params = StreamableHttpServerParams( url=url, timeout=30.0, sse_read_timeout=300.0, terminate_on_close=True, headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")} ) ``` ### 6. Create the model client and agent What's happening: - OpenAIChatCompletionClient wraps the OpenAI model for Autogen - McpWorkbench connects the agent to the MCP tools - AssistantAgent is configured with the Airtable tools from the workbench ```python # Create model client model_client = OpenAIChatCompletionClient( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY") ) # Use McpWorkbench as context manager async with McpWorkbench(server_params) as workbench: # Create Airtable assistant agent with MCP tools agent = AssistantAgent( name="airtable_assistant", description="An AI assistant that helps with Airtable operations.", model_client=model_client, workbench=workbench, model_client_stream=True, max_tool_iterations=10 ) ``` ### 7. Run the interactive chat loop What's happening: - The script prompts you in a loop with You: - Autogen passes your input to the model, which decides which Airtable tools to call via MCP - agent.run_stream(...) yields streaming messages as the agent thinks and calls tools - Typing exit, quit, or bye ends the loop ```python print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Airtable related question or task to the agent.\n") # Conversation loop while True: user_input = input("You: ").strip() if user_input.lower() in ["exit", "quit", "bye"]: print("\nGoodbye!") break if not user_input: continue print("\nAgent is thinking...\n") # Run the agent with streaming try: response_text = "" async for message in agent.run_stream(task=user_input): if hasattr(message, "content") and message.content: response_text = message.content # Print the final response if response_text: print(f"Agent: {response_text}\n") else: print("Agent: I encountered an issue processing your request.\n") except Exception as e: print(f"Agent: Sorry, I encountered an error: {str(e)}\n") ``` ## Complete Code ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from autogen_agentchat.agents import AssistantAgent from autogen_ext.models.openai import OpenAIChatCompletionClient from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams load_dotenv() async def main(): # Initialize Composio and create a Airtable session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["airtable"] ) url = session.mcp.url # Configure MCP server parameters for Streamable HTTP server_params = StreamableHttpServerParams( url=url, timeout=30.0, sse_read_timeout=300.0, terminate_on_close=True, headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")} ) # Create model client model_client = OpenAIChatCompletionClient( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY") ) # Use McpWorkbench as context manager async with McpWorkbench(server_params) as workbench: # Create Airtable assistant agent with MCP tools agent = AssistantAgent( name="airtable_assistant", description="An AI assistant that helps with Airtable operations.", model_client=model_client, workbench=workbench, model_client_stream=True, max_tool_iterations=10 ) print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Airtable related question or task to the agent.\n") # Conversation loop while True: user_input = input("You: ").strip() if user_input.lower() in ['exit', 'quit', 'bye']: print("\nGoodbye!") break if not user_input: continue print("\nAgent is thinking...\n") # Run the agent with streaming try: response_text = "" async for message in agent.run_stream(task=user_input): if hasattr(message, 'content') and message.content: response_text = message.content # Print the final response if response_text: print(f"Agent: {response_text}\n") else: print("Agent: I encountered an issue processing your request.\n") except Exception as e: print(f"Agent: Sorry, I encountered an error: {str(e)}\n") if __name__ == "__main__": asyncio.run(main()) ``` ## Conclusion You now have an Autogen assistant wired into Airtable through Composio's Tool Router and MCP. From here you can: - Add more toolkits to the toolkits list, for example notion or hubspot - Refine the agent description to point it at specific workflows - Wrap this script behind a UI, Slack bot, or internal tool Once the pattern is clear for Airtable, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build Airtable MCP Agent with another framework - [ChatGPT](https://composio.dev/toolkits/airtable/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/airtable/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/airtable/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/airtable/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/airtable/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/airtable/framework/codex) - [Cursor](https://composio.dev/toolkits/airtable/framework/cursor) - [VS Code](https://composio.dev/toolkits/airtable/framework/vscode) - [OpenCode](https://composio.dev/toolkits/airtable/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/airtable/framework/openclaw) - [Hermes](https://composio.dev/toolkits/airtable/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/airtable/framework/cli) - [Google ADK](https://composio.dev/toolkits/airtable/framework/google-adk) - [LangChain](https://composio.dev/toolkits/airtable/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/airtable/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/airtable/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/airtable/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/airtable/framework/crew-ai) ## Related Toolkits - [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly. - [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place. - [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals. - [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem. - [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity. - [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently. - [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place. - [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time. - [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time. - [Agiled](https://composio.dev/toolkits/agiled) - Agiled is an all-in-one business management platform for CRM, projects, and finance. It helps you streamline workflows, consolidate client data, and manage business processes in one place. - [Ascora](https://composio.dev/toolkits/ascora) - Ascora is a cloud-based field service management platform for service businesses. It streamlines scheduling, invoicing, and customer operations in one place. - [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place. - [Beeminder](https://composio.dev/toolkits/beeminder) - Beeminder is an online goal-tracking platform that uses monetary pledges to keep you motivated. Stay accountable and hit your targets with real financial incentives. - [Boxhero](https://composio.dev/toolkits/boxhero) - Boxhero is a cloud-based inventory management platform for SMBs, offering real-time updates, barcode scanning, and team collaboration. It helps businesses streamline stock tracking and analytics for smarter inventory decisions. - [Breathe HR](https://composio.dev/toolkits/breathehr) - Breathe HR is cloud-based HR software for SMEs to manage employee data, absences, and performance. It simplifies HR admin, making it easy to keep employee records accurate and up to date. - [Breeze](https://composio.dev/toolkits/breeze) - Breeze is a project management platform designed to help teams plan, track, and collaborate on projects. It streamlines workflows and keeps everyone on the same page. - [Bugherd](https://composio.dev/toolkits/bugherd) - Bugherd is a visual feedback and bug tracking tool for websites. It helps teams and clients report website issues directly on live sites for faster fixes. - [Canny](https://composio.dev/toolkits/canny) - Canny is a platform for managing customer feedback and feature requests. It helps teams prioritize product decisions based on real user insights. - [Chmeetings](https://composio.dev/toolkits/chmeetings) - Chmeetings is a church management platform for events, members, donations, and volunteers. It streamlines church operations and improves community engagement. - [ClickSend](https://composio.dev/toolkits/clicksend) - ClickSend is a cloud-based SMS and email marketing platform for businesses. It streamlines communication by enabling quick message delivery and contact management. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Airtable MCP? With a standalone Airtable MCP server, the agents and LLMs can only access a fixed set of Airtable tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Airtable and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with Autogen? Yes, you can. Autogen fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Airtable tools. ### Can I manage the permissions and scopes for Airtable while using Tool Router? Yes, absolutely. You can configure which Airtable scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do. ### How safe is my data with Composio Tool Router? All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Airtable data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)