How to integrate Telegram MCP with CrewAI

This guide walks you through connecting Telegram to CrewAI using the Composio tool router. By the end, you'll have a working Telegram agent that can send a welcome message to new group members, forward latest announcement to all admins, get total member count of your group through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Telegram account through Composio's Telegram MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Telegram is a fast, secure cloud messaging app for individuals and groups. It offers robust privacy and real-time chat features.

18 Tools

Introduction

This guide walks you through connecting Telegram to CrewAI using the Composio tool router. By the end, you'll have a working Telegram agent that can send a welcome message to new group members, forward latest announcement to all admins, get total member count of your group through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Telegram account through Composio's Telegram MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Telegram with

ChatGPTOpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenCodeCursorVS CodeOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndex

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Telegram connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Telegram
  • Build a conversational loop where your agent can execute Telegram operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

What is the Telegram MCP server, and what's possible with it?

The Telegram MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Telegram account. It provides structured and secure access to your chats and bot functionality, so your agent can send messages, manage conversations, retrieve chat data, and interact with users or groups on your behalf.

  • Automated message sending and editing: Let your agent send new messages or edit existing ones in any chat where your bot is present, making real-time communication a breeze.
  • Chat and group management: Effortlessly manage group chats by retrieving chat details, getting administrators, exporting invite links, or counting group members.
  • Advanced chat history and message handling: Ask your agent to fetch chat history, forward messages between chats, or delete messages for streamlined moderation and record-keeping.
  • Bot and user interaction: Enable the agent to answer callback queries from inline keyboards and fetch basic bot information for smarter, context-aware responses.

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

What is Composio SDK?

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

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

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

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

Step-by-step Guide

Step by step08 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Telegram connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Telegram via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model
5

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

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

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")
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Telegram MCP URL
6

Create a Composio Tool Router session for Telegram

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["telegram"])

url = session.mcp.url
What's happening:
  • You create a Telegram only session through Composio
  • Composio returns an MCP HTTP URL that exposes Telegram tools
7

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.
8

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's Happening:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

Here's the complete code to get you started with Telegram and CrewAI:

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

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

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_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.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["telegram"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Telegram through Composio's Tool Router. The agent can perform Telegram operations through natural language commands.

Next steps:

  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations
TOOLS

Supported Tools

Every Telegram action and event your agent gets out of the box.

Answer Callback Query

Use this method to send answers to callback queries sent from inline keyboards.

Export Chat Invite Link

Generate a new primary invite link for a chat; any previously generated primary link is revoked.

Delete Message

Delete a message, including service messages.

Edit Message

Edit text messages sent by the bot.

Forward Message

Forward messages of any kind.

Get Chat Info

Get up to date information about the chat (current name of the user for one-on-one conversations, current username of a user, group or channel, etc.

Get Chat Administrators

Get a list of administrators in a chat.

Get Chat History

Get chat history messages via the getUpdates polling method, filtered by chat_id.

Get Chat Member

Get a chat member's status/role (including the bot itself) to preflight permissions and troubleshoot 403/empty-history issues.

Get Chat Members Count

Get the number of members in a chat.

Get Bot Info

Get basic information about the bot using the Bot API getMe method.

Get Updates

Use this method to receive incoming updates using long polling.

Send Document

Send general files (documents) to a Telegram chat using the Bot API.

Send Location

Send point on the map location to a Telegram chat using the Bot API.

Send Message

Send a text message to a Telegram chat using the Bot API.

Send Photo

Send photos to a Telegram chat using the Bot API.

Send Poll

Send a native poll to a Telegram chat using the Bot API.

Set Bot Commands

Use this method to change the list of the bot's commands.

FRAMEWORKS

How to build Telegram MCP Agent with another framework

ChatGPT logo

ChatGPT

Use Telegram MCP with ChatGPT

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Telegram MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Telegram MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Telegram MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Telegram MCP with Claude Cowork

Codex logo

Codex

Use Telegram MCP with Codex

Cursor logo

Cursor

Use Telegram MCP with Cursor

OpenClaw logo

OpenClaw

Use Telegram MCP with OpenClaw

Hermes logo

Hermes

Use Telegram MCP with Hermes

CLI logo

CLI

Use Telegram MCP with CLI

Google ADK logo

Google ADK

Use Telegram MCP with Google ADK

LangChain logo

LangChain

Use Telegram MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Telegram MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Telegram MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Telegram MCP with LlamaIndex

OpenCode logo

OpenCode

Use Telegram MCP with OpenCode

VS Code logo

VS Code

Use Telegram MCP with VS Code

FAQ

Frequently asked questions

With a standalone Telegram MCP server, the agents and LLMs can only access a fixed set of Telegram tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Telegram and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. CrewAI 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 Telegram tools.

Yes, absolutely. You can configure which Telegram 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.

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 Telegram data and credentials are handled as safely as possible.

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