# How to integrate Airtable MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Airtable MCP with OpenAI Agents SDK",
  "toolkit": "Airtable",
  "toolkit_slug": "airtable",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/airtable/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/airtable/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:00:41.159Z"
}
```

## 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Airtable agent that can add new contacts from a signup list, create a project tracking table in workspace, delete outdated records from clients table through natural language commands.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

- [ChatGPT](https://composio.dev/toolkits/airtable/framework/chatgpt)
- [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 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

| 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 agent to Airtable. It provides structured and secure access so your agent can perform Airtable operations on your behalf through a secure, permission-based interface.
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

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

### 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).
- Go to Settings and copy your API key.

### 2. Install dependencies

Install the Composio SDK and the OpenAI Agents SDK.
```python
pip install composio_openai_agents openai-agents python-dotenv
```

```typescript
npm install @composio/openai-agents @openai/agents dotenv
```

### 3. Set up environment variables

Create a .env file and add your OpenAI and Composio API keys.
```bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com
```

### 4. Import dependencies

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.
```python
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
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
```

### 5. Set up the Composio instance

No description provided.
```python
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())
```

```typescript
dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
```

### 6. Create a Tool Router session

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

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for Airtable
const session = await composio.create(userId as string, {
  toolkits: ['airtable'],
});
const mcpUrl = session.mcp.url;
```

### 7. Configure the agent

No description provided.
```python
# 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",
            }
        )
    ],
)
```

```typescript
// Configure agent with MCP tool
const agent = new 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({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
```

### 8. Start chat loop and handle conversation

No description provided.
```python
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())
```

```typescript
// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

  if (!text) {
    rl.prompt();
    return;
  }

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
```

## Complete Code

```python
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())
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['airtable'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new 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({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

    if (!text) {
      rl.prompt();
      return;
    }

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\n');
    }

    rl.prompt();
  });

  rl.on('close', () => {
    console.log('\nSession ended.');
    process.exit(0);
  });
}

main().catch((err) => {
  console.error('Fatal error:', err);
  process.exit(1);
});
```

## 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](https://composio.dev/toolkits/airtable/framework/chatgpt)
- [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 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.

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[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)
