# How to integrate Airtable MCP with LlamaIndex

```json
{
  "title": "How to integrate Airtable MCP with LlamaIndex",
  "toolkit": "Airtable",
  "toolkit_slug": "airtable",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/airtable/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/airtable/framework/llama-index.md",
  "updated_at": "2026-05-12T10:00:41.159Z"
}
```

## Introduction

This guide walks you through connecting Airtable to LlamaIndex 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Airtable agent that can add new contacts from a signup list, create a project tracking table in workspace, delete outdated records from clients table through natural language commands.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 LlamaIndex 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)
- [CrewAI](https://composio.dev/toolkits/airtable/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Set your OpenAI and Composio API keys
- Install LlamaIndex and Composio packages
- Create a Composio Tool Router session for Airtable
- Connect LlamaIndex to the Airtable MCP server
- Build a Airtable-powered agent using LlamaIndex
- Interact with Airtable through natural language

## What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.
Key features include:
- ReAct Agent: Reasoning and acting pattern for tool-using agents
- MCP Tools: Native support for Model Context Protocol
- Context Management: Maintain conversation context across interactions
- Async Support: Built for async/await patterns

## 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 you begin, make sure you have:
- Python 3.8/Node 16 or higher installed
- A Composio account with the API key
- An OpenAI API key
- A Airtable account and project
- Basic familiarity with async Python/Typescript

### 1. Getting API Keys for OpenAI, Composio, and Airtable

No description provided.

### 2. Installing dependencies

No description provided.
```python
pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv
```

```typescript
npm install @composio/llamaindex @llamaindex/openai @llamaindex/tools @llamaindex/workflow dotenv
```

### 3. Set environment variables

Create a .env file in your project root:
These credentials will be used to:
- Authenticate with OpenAI's GPT-5 model
- Connect to Composio's Tool Router
- Identify your Composio user session for Airtable access
```bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id
```

### 4. Import modules

No description provided.
```python
import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()
```

```typescript
import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();
```

### 5. Load environment variables and initialize Composio

No description provided.
```python
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")
```

```typescript
const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!COMPOSIO_API_KEY) throw new Error("COMPOSIO_API_KEY is not set");
if (!COMPOSIO_USER_ID) throw new Error("COMPOSIO_USER_ID is not set");
```

### 6. Create a Tool Router session and build the agent function

What's happening here:
- We create a Composio client using your API key and configure it with the LlamaIndex provider
- We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, airtable)
- The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
- LlamaIndex will connect to this endpoint to dynamically discover and use the available Airtable tools.
- The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.
```python
async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["airtable"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Airtable actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Airtable actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)
```

```typescript
async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["airtable"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
        description : "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Airtable actions." ,
    llm,
    tools,
  });

  return agent;
}
```

### 7. Create an interactive chat loop

No description provided.
```python
async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")
```

```typescript
async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}
```

### 8. Define the main entry point

What's happening here:
- We're orchestrating the entire application flow
- The agent gets built with proper error handling
- Then we kick off the interactive chat loop so you can start talking to Airtable
```python
async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err) {
    console.error("Failed to start agent:", err);
    process.exit(1);
  }
}

main();
```

### 9. Run the agent

When prompted, authenticate and authorise your agent with Airtable, then start asking questions.
```bash
python llamaindex_agent.py
```

```typescript
npx ts-node llamaindex-agent.ts
```

## Complete Code

```python
import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["airtable"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Airtable actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Airtable actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";
import { LlamaindexProvider } from "@composio/llamaindex";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) {
    throw new Error("OPENAI_API_KEY is not set in the environment");
  }
if (!COMPOSIO_API_KEY) {
    throw new Error("COMPOSIO_API_KEY is not set in the environment");
  }
if (!COMPOSIO_USER_ID) {
    throw new Error("COMPOSIO_USER_ID is not set in the environment");
  }

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["airtable"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
    description:
      "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Airtable actions." ,
    llm,
    tools,
  });

  return agent;
}

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err: any) {
    console.error("Failed to start agent:", err?.message ?? err);
    process.exit(1);
  }
}

main();
```

## Conclusion

You've successfully connected Airtable to LlamaIndex through Composio's Tool Router MCP layer.
Key takeaways:
- Tool Router dynamically exposes Airtable tools through an MCP endpoint
- LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
- The agent becomes more capable without increasing prompt size
- Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

## 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)
- [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 LlamaIndex?

Yes, you can. LlamaIndex 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)