How to integrate Airtable MCP with OpenAI Agents SDK

Trusted by
AWS
Glean
Zoom
Airtable
GET STARTED FOR FREEGET A DEMO

30 min · no commitment · see it on your stack

Airtable logo
OpenAI Agents SDK logo
divider

Introduction

This guide walks you through connecting Airtable to the OpenAI Agents SDK 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Airtable agent that can add new contacts from a signup list, create a project tracking table in workspace, delete outdated records from clients table through natural language commands.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 OpenAI Agents SDK 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

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Airtable
  • Configure an AI agent that can use Airtable as a tool
  • Run a live chat session where you can ask the agent to perform Airtable operations

What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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creation and management: Easily instruct your agent to add new records, create multiple entries at once, or delete outdated information across any Airtable table.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 & Triggers

Tools
Triggers
Create baseCreates a new Airtable base with specified tables and fields within a workspace.
Create CommentTool to create a comment on a specific Airtable record.
Create FieldCreates a new field within a specified table in an Airtable base.
Create Record From Natural LanguageCreates a new record in an Airtable table from a natural language description.
Create recordsTool to create multiple records (up to 10) in a specified Airtable table.
Create tableCreates a new table within a specified existing Airtable base, allowing definition of its name, description, and field structure.
Delete CommentTool to delete a comment from a record in an Airtable table.
Delete multiple recordsTool to delete up to 10 specified records from a table within an Airtable base.
Delete RecordPermanently deletes a specific record from an existing table within an existing Airtable base.
Get Base SchemaRetrieves the detailed schema for a specified Airtable base, including its tables, fields, field types, and configurations, using the `baseId`.
Get RecordRetrieves a specific record from an Airtable table by its record ID.
Get user informationRetrieves information, such as ID and permission scopes, for the currently authenticated Airtable user from the `/meta/whoami` endpoint.
List basesRetrieves all Airtable bases accessible to the authenticated user, which may include an 'offset' for pagination.
List CommentsTool to list comments on a specific Airtable record.
List recordsTool to list records from an Airtable table with filtering, sorting, and pagination.
Update CommentTool to update an existing comment on a specific Airtable record.
Update FieldUpdates a field's name or description in an Airtable table.
Update multiple recordsTool to update up to 10 records in an Airtable table with selective field modifications.
Update multiple records (PUT)Tool to destructively update multiple records in Airtable using PUT, clearing unspecified fields.
Update recordModifies specified fields of an existing record in an Airtable base and table; the base, table, and record must exist.
Update record (PUT)Updates an existing record in an Airtable base using PUT method.
Update TableUpdates the name, description, and/or date dependency settings of a table in Airtable.
Upload attachmentUploads a file attachment to a specified field in an Airtable record.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Airtable project
  • Some knowledge of Python or Typescript

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Airtable.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Airtable Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["airtable"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only airtable.
  • The router checks the user's Airtable connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Airtable.
  • This approach keeps things lightweight and lets the agent request Airtable tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Airtable. "
        "Help users perform Airtable operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Airtable and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Airtable operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Airtable.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Airtable and OpenAI Agents SDK:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["airtable"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Airtable. "
        "Help users perform Airtable operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Airtable MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Airtable.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

How to build Airtable MCP Agent with another framework

ChatGPT logo

ChatGPT

Use Airtable MCP with ChatGPT

Claude Agent SDK logo

Claude Agent SDK

Use Airtable MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Airtable MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Airtable MCP with Claude Cowork

Codex logo

Codex

Use Airtable MCP with Codex

Cursor logo

Cursor

Use Airtable MCP with Cursor

OpenClaw logo

OpenClaw

Use Airtable MCP with OpenClaw

Hermes logo

Hermes

Use Airtable MCP with Hermes

CLI logo

CLI

Use Airtable MCP with CLI

Google ADK logo

Google ADK

Use Airtable MCP with Google ADK

LangChain logo

LangChain

Use Airtable MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Airtable MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Airtable MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Airtable MCP with LlamaIndex

CrewAI logo

CrewAI

Use Airtable MCP with CrewAI

OpenCode logo

OpenCode

Use Airtable MCP with OpenCode

VS Code logo

VS Code

Use Airtable MCP with VS Code

FAQ

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 OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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.

Used by agents from

Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.

Get started for freeGet a demo↗