# How to integrate Gmail MCP with LlamaIndex

```json
{
  "title": "How to integrate Gmail MCP with LlamaIndex",
  "toolkit": "Gmail",
  "toolkit_slug": "gmail",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/gmail/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/gmail/framework/llama-index.md",
  "updated_at": "2026-05-06T08:13:39.350Z"
}
```

## Introduction

This guide walks you through connecting Gmail to LlamaIndex using the Composio tool router. By the end, you'll have a working Gmail agent that can read emails, search your inbox, draft messages, manage labels, and organize threads through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Gmail account through Composio's Gmail MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Gmail with

- [ChatGPT](https://composio.dev/toolkits/gmail/framework/chatgpt)
- [OpenAI Agents SDK](https://composio.dev/toolkits/gmail/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/gmail/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/gmail/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/gmail/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/gmail/framework/codex)
- [Cursor](https://composio.dev/toolkits/gmail/framework/cursor)
- [VS Code](https://composio.dev/toolkits/gmail/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/gmail/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/gmail/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/gmail/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/gmail/framework/cli)
- [Google ADK](https://composio.dev/toolkits/gmail/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/gmail/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/gmail/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/gmail/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/gmail/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 Gmail
- Connect LlamaIndex to the Gmail MCP server
- Build a Gmail-powered agent using LlamaIndex
- Interact with Gmail 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 Gmail MCP server, and what's possible with it?

The Gmail MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Gmail account. It provides structured and secure access to your email, so your agent can search, read, draft, organize, and even manage contacts in your mailbox—all on your behalf.
- Advanced email search and retrieval: Effortlessly instruct your agent to fetch emails by sender, subject, label, date, or keywords, and even retrieve full message content or threads.
- Automated drafting and sending: Have your agent create new email drafts, craft replies, add CC/BCC, include attachments, and handle threading to streamline communication.
- Smart label and inbox organization: Let the agent create new labels, apply or remove labels from emails, and keep your inbox clutter-free by archiving or moving messages.
- Contact and thread management: Fetch your Gmail contacts, pull entire conversation threads, or download specific attachments to make follow-ups a breeze.
- Email and draft cleanup: Direct your agent to permanently delete emails or drafts, helping you maintain a tidy mailbox with minimal effort.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `GMAIL_ADD_LABEL_TO_EMAIL` | Modify email labels | Adds and/or removes specified gmail labels for a message; ensure `message id` and all `label ids` are valid (use 'listlabels' for custom label ids). |
| `GMAIL_CREATE_EMAIL_DRAFT` | Create email draft | Creates a gmail email draft, supporting to/cc/bcc, subject, plain/html body (ensure `is html=true` for html), attachments, and threading. |
| `GMAIL_CREATE_LABEL` | Create label | Creates a new label with a unique name in the specified user's gmail account. |
| `GMAIL_DELETE_DRAFT` | Delete Draft | Permanently deletes a specific gmail draft using its id; ensure the draft exists and the user has necessary permissions for the given `user id`. |
| `GMAIL_DELETE_MESSAGE` | Delete message | Permanently deletes a specific email message by its id from a gmail mailbox; for `user id`, use 'me' for the authenticated user or an email address to which the authenticated user has delegated access. |
| `GMAIL_FETCH_EMAILS` | Fetch emails | Fetches a list of email messages from a gmail account, supporting filtering, pagination, and optional full content retrieval. |
| `GMAIL_FETCH_MESSAGE_BY_MESSAGE_ID` | Fetch message by message ID | Fetches a specific email message by its id, provided the `message id` exists and is accessible to the authenticated `user id`. |
| `GMAIL_FETCH_MESSAGE_BY_THREAD_ID` | Fetch Message by Thread ID | Retrieves messages from a gmail thread using its `thread id`, where the thread must be accessible by the specified `user id`. |
| `GMAIL_GET_ATTACHMENT` | Get Gmail attachment | Retrieves a specific attachment by id from a message in a user's gmail mailbox, requiring valid message and attachment ids. |
| `GMAIL_GET_CONTACTS` | Get contacts | Fetches contacts (connections) for the authenticated google account, allowing selection of specific data fields and pagination. |
| `GMAIL_GET_PEOPLE` | Get People | Retrieves either a specific person's details (using `resource name`) or lists 'other contacts' (if `other contacts` is true), with `person fields` specifying the data to return. |
| `GMAIL_GET_PROFILE` | Get Profile | Retrieves key gmail profile information (email address, message/thread totals, history id) for a user. |
| `GMAIL_LIST_DRAFTS` | List drafts | Retrieves a paginated list of email drafts from a user's gmail account. use verbose=true to get full draft details including subject, body, sender, and timestamp. |
| `GMAIL_LIST_LABELS` | List Gmail labels | Retrieves a list of all system and user-created labels for the specified gmail account. |
| `GMAIL_LIST_THREADS` | List threads | Retrieves a list of email threads from a gmail account, identified by `user id` (email address or 'me'), supporting filtering and pagination. |
| `GMAIL_MODIFY_THREAD_LABELS` | Modify thread labels | Adds or removes specified existing label ids from a gmail thread, affecting all its messages; ensure the thread id is valid. |
| `GMAIL_MOVE_TO_TRASH` | Move to Trash | Moves an existing, non-deleted email message to the trash for the specified user. |
| `GMAIL_PATCH_LABEL` | Patch Label | Patches the specified label. |
| `GMAIL_REMOVE_LABEL` | Remove label | Permanently deletes a specific, existing user-created gmail label by its id for a user; cannot delete system labels. |
| `GMAIL_REPLY_TO_THREAD` | Reply to email thread | Sends a reply within a specific gmail thread using the original thread's subject, requiring a valid `thread id` and correctly formatted email addresses. supports attachments via the `attachment` parameter with valid `s3key`, `mimetype`, and `name`. |
| `GMAIL_SEARCH_PEOPLE` | Search People | Searches contacts by matching the query against names, nicknames, emails, phone numbers, and organizations, optionally including 'other contacts'. |
| `GMAIL_SEND_DRAFT` | Send Draft | Sends the specified, existing draft to the recipients in the to, cc, and bcc headers. |
| `GMAIL_SEND_EMAIL` | Send Email | Sends an email via gmail api using the authenticated user's google profile display name, requiring `is html=true` if the body contains html and valid `s3key`, `mimetype`, `name` for any attachment. |

## Supported Triggers

| Trigger slug | Name | Description |
|---|---|---|
| `GMAIL_EMAIL_SENT_TRIGGER` | Email Sent | Triggers when a Gmail message is sent by the authenticated user. It polls the 'SENT' label and emits metadata including sender, recipients, subject, timestamp, and thread ID. |
| `GMAIL_NEW_GMAIL_MESSAGE` | New Gmail Message Received Trigger | Triggers when a new message is received in Gmail. |

## Creating MCP Server - Stand-alone vs Composio SDK

The Gmail MCP server is an implementation of the Model Context Protocol that connects your AI agent to Gmail. It provides structured and secure access so your agent can perform Gmail 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 Gmail account and project
- Basic familiarity with async Python/Typescript

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

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 Gmail 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, gmail)
- 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 Gmail 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=["gmail"],
    )

    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 Gmail actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Gmail 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: ["gmail"],
    },
  );

  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 Gmail 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 Gmail
```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 Gmail, 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=["gmail"],
    )

    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 Gmail actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Gmail 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: ["gmail"],
    },
  );

  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 Gmail 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 Gmail to LlamaIndex through Composio's Tool Router MCP layer.
Key takeaways:
- Tool Router dynamically exposes Gmail 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 Gmail MCP Agent with another framework

- [ChatGPT](https://composio.dev/toolkits/gmail/framework/chatgpt)
- [OpenAI Agents SDK](https://composio.dev/toolkits/gmail/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/gmail/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/gmail/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/gmail/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/gmail/framework/codex)
- [Cursor](https://composio.dev/toolkits/gmail/framework/cursor)
- [VS Code](https://composio.dev/toolkits/gmail/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/gmail/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/gmail/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/gmail/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/gmail/framework/cli)
- [Google ADK](https://composio.dev/toolkits/gmail/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/gmail/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/gmail/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/gmail/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/gmail/framework/crew-ai)

## Related Toolkits

- [Outlook](https://composio.dev/toolkits/outlook) - Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management.
- [Slack](https://composio.dev/toolkits/slack) - Slack is a channel-based messaging platform for teams and organizations. It helps people collaborate in real time, share files, and connect all their tools in one place.
- [Gong](https://composio.dev/toolkits/gong) - Gong is a platform for video meetings, call recording, and team collaboration. It helps teams capture conversations, analyze calls, and turn insights into action.
- [Microsoft teams](https://composio.dev/toolkits/microsoft_teams) - Microsoft Teams is a collaboration platform that combines chat, meetings, and file sharing within Microsoft 365. It keeps distributed teams connected and productive through seamless virtual communication.
- [Slackbot](https://composio.dev/toolkits/slackbot) - Slackbot is a conversational automation tool for Slack that handles reminders, notifications, and automated responses. It boosts team productivity by streamlining onboarding, answering FAQs, and managing timely alerts—all right inside Slack.
- [2chat](https://composio.dev/toolkits/_2chat) - 2chat is an API platform for WhatsApp and multichannel text messaging. It streamlines chat automation, group management, and real-time messaging for developers.
- [Agent mail](https://composio.dev/toolkits/agent_mail) - Agent mail provides AI agents with dedicated email inboxes for sending, receiving, and managing emails. It empowers agents to communicate autonomously with people, services, and other agents—no human intervention needed.
- [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.
- [Chatwork](https://composio.dev/toolkits/chatwork) - Chatwork is a team communication platform with group chats, file sharing, and task management. It helps businesses boost collaboration and streamline productivity.
- [Clickmeeting](https://composio.dev/toolkits/clickmeeting) - ClickMeeting is a cloud-based platform for running online meetings and webinars. It helps businesses and individuals host, manage, and engage virtual audiences with ease.
- [Confluence](https://composio.dev/toolkits/confluence) - Confluence is Atlassian's team collaboration and knowledge management platform. It helps your team organize, share, and update documents and project content in one secure workspace.
- [Dailybot](https://composio.dev/toolkits/dailybot) - DailyBot streamlines team collaboration with chat-based standups, reminders, and polls. It keeps work flowing smoothly in your favorite messaging platforms.
- [Dialmycalls](https://composio.dev/toolkits/dialmycalls) - Dialmycalls is a mass notification service for sending voice and text messages to contacts. It helps teams and organizations quickly broadcast urgent alerts and updates.
- [Dialpad](https://composio.dev/toolkits/dialpad) - Dialpad is a cloud-based business phone and contact center system for teams. It unifies voice, video, messaging, and meetings across your devices.
- [Discord](https://composio.dev/toolkits/discord) - Discord is a real-time messaging and VoIP platform for communities and teams. It lets users chat, share media, and collaborate across public and private channels.
- [Discordbot](https://composio.dev/toolkits/discordbot) - Discordbot is an automation tool for Discord servers that handles moderation, messaging, and user engagement. It helps communities run smoothly by automating routine and complex tasks.
- [Echtpost](https://composio.dev/toolkits/echtpost) - Echtpost is a secure digital communication platform for encrypted document and message exchange. It ensures confidential data stays private and protected during transmission.
- [Egnyte](https://composio.dev/toolkits/egnyte) - Egnyte is a cloud-based platform for secure file sharing, storage, and governance. It helps teams collaborate efficiently while maintaining data compliance and security.
- [Google Meet](https://composio.dev/toolkits/googlemeet) - Google Meet is a secure video conferencing platform for virtual meetings, chat, and screen sharing. It helps teams connect, collaborate, and communicate seamlessly from anywhere.
- [Heartbeat](https://composio.dev/toolkits/heartbeat) - Heartbeat is a plug-and-play platform for building and managing online communities. It helps you organize users, channels, events, and discussions in one place.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Gmail MCP?

With a standalone Gmail MCP server, the agents and LLMs can only access a fixed set of Gmail tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Gmail 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 Gmail tools.

### Can I manage the permissions and scopes for Gmail while using Tool Router?

Yes, absolutely. You can configure which Gmail 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 Gmail 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)