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How to integrate Telegram MCP with Vercel AI SDK v6

Connect Vercel AI SDK v6 to Telegram MCP. Send a welcome message to new group members, forward latest announcement to all admins, and more using natural language, with authentication handled for you.

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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.

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Introduction

This guide walks you through connecting Telegram to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Telegram agent that can send messages, share photos and documents, edit and forward messages, read chat history, and create polls through natural language commands.

This guide will help you understand how to give your Vercel AI SDK 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.

TL;DR

Here's what you'll learn:

How to set up and configure a Vercel AI SDK agent with Telegram integration
Using Composio's Tool Router to dynamically load and access Telegram tools
Creating an MCP client connection using HTTP transport
Building an interactive CLI chat interface with conversation history management
Handling tool calls and results within the Vercel AI SDK framework

What is Vercel AI SDK?

The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state.

Key features include:

streamText: Core function for streaming responses with real-time tool support
MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp
Step Counting: Control multi-step tool execution with stopWhen: stepCountIs()
OpenAI Provider: Native integration with OpenAI models

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:

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

Step-by-step Guide

Step by step09 STEPS

Prerequisites

Before you begin, make sure you have:

Node.js and npm installed
A Composio account with API key
An OpenAI API key

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.

Install required dependencies

bash

npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv

First, install the necessary packages for your project.

What you're installing:

@ai-sdk/openai: Vercel AI SDK's OpenAI provider
@ai-sdk/mcp: MCP client for Vercel AI SDK
@composio/core: Composio SDK for tool integration
ai: Core Vercel AI SDK
dotenv: Environment variable management

Set up environment variables

bash

OPENAI_API_KEY=your_openai_api_key_here
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here

Create a .env file in your project root.

What's needed:

OPENAI_API_KEY: Your OpenAI API key for GPT model access
COMPOSIO_API_KEY: Your Composio API key for tool access
COMPOSIO_USER_ID: A unique identifier for the user session

Import required modules and validate environment

typescript

import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey,
});

What's happening:

We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio
The dotenv/config import automatically loads environment variables
The MCP client import enables connection to Composio's tool server

Create Tool Router session and initialize MCP client

typescript

async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["telegram"],
  });

  const mcpUrl = session.mcp.url;

What's happening:

We're creating a Tool Router session that gives your agent access to Telegram tools
The create method takes the user ID and specifies which toolkits should be available
The returned mcp object contains the URL and authentication headers needed to connect to the MCP server
This session provides access to all Telegram-related tools through the MCP protocol

Connect to MCP server and retrieve tools

typescript

const mcpClient = await createMCPClient({
  transport: {
    type: "http",
    url: mcpUrl,
    headers: session.mcp.headers, // Authentication headers for the Composio MCP server
  },
});

const tools = await mcpClient.tools();

What's happening:

We're creating an MCP client that connects to our Composio Tool Router session via HTTP
The mcp.url provides the endpoint, and mcp.headers contains authentication credentials
The type: "http" is important - Composio requires HTTP transport
tools() retrieves all available Telegram tools that the agent can use

Initialize conversation and CLI interface

typescript

let messages: ModelMessage[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log(
  "Ask any questions related to telegram, like summarize my last 5 emails, send an email, etc... :)))\n",
);

const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: "> ",
});

rl.prompt();

What's happening:

We initialize an empty messages array to maintain conversation history
A readline interface is created to accept user input from the command line
Instructions are displayed to guide the user on how to interact with the agent

Handle user input and stream responses with real-time tool feedback

typescript

rl.on("line", async (userInput: string) => {
  const trimmedInput = userInput.trim();

  if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
    console.log("\nGoodbye!");
    rl.close();
    process.exit(0);
  }

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

  messages.push({ role: "user", content: trimmedInput });
  console.log("\nAgent is thinking...\n");

  try {
    const stream = streamText({
      model: openai("gpt-5"),
      messages,
      tools,
      toolChoice: "auto",
      stopWhen: stepCountIs(10),
      onStepFinish: (step) => {
        for (const toolCall of step.toolCalls) {
          console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

  rl.on("close", async () => {
    await mcpClient.close();
    console.log("\n👋 Session ended.");
    process.exit(0);
  });
}

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

What's happening:

We use streamText instead of generateText to stream responses in real-time
toolChoice: "auto" allows the model to decide when to use Telegram tools
stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations
onStepFinish callback displays which tools are being used in real-time
We iterate through the text stream to create a typewriter effect as the agent responds
The complete response is added to conversation history to maintain context
Errors are caught and displayed with helpful retry suggestions

Complete Code

Here's the complete code to get you started with Telegram and Vercel AI SDK:

typescript

import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Composio } from "@composio/core";
import * as readline from "readline";
import { streamText, type ModelMessage, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";

const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set");
if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set");

const composio = new Composio({
  apiKey: composioAPIKey,
});

async function main() {
  // Create a tool router session for the user
  const session = await composio.create(composioUserID!, {
    toolkits: ["telegram"],
  });

  const mcpUrl = session.mcp.url;

  const mcpClient = await createMCPClient({
    transport: {
      type: "http",
      url: mcpUrl,
      headers: session.mcp.headers, // Authentication headers for the Composio MCP server
    },
  });

  const tools = await mcpClient.tools();

  let messages: ModelMessage[] = [];

  console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
  console.log(
    "Ask any questions related to telegram, like summarize my last 5 emails, send an email, etc... :)))\n",
  );

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) {
      console.log("\nGoodbye!");
      rl.close();
      process.exit(0);
    }

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

    messages.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    try {
      const stream = streamText({
        model: openai("gpt-5"),
        messages,
        tools,
        toolChoice: "auto",
        stopWhen: stepCountIs(10),
        onStepFinish: (step) => {
          for (const toolCall of step.toolCalls) {
            console.log(`[Using tool: ${toolCall.toolName}]`);
          }
          if (step.toolCalls.length > 0) {
            console.log(""); // Add space after tool calls
          }
        },
      });

      for await (const chunk of stream.textStream) {
        process.stdout.write(chunk);
      }

      console.log("\n\n---\n");

      // Get final result for message history
      const response = await stream.response;
      if (response?.messages?.length) {
        messages.push(...response.messages);
      }
    } catch (error) {
      console.error("\nAn error occurred while talking to the agent:");
      console.error(error);
      console.log(
        "\nYou can try again or restart the app if it keeps happening.\n",
      );
    } finally {
      rl.prompt();
    }
  });

  rl.on("close", async () => {
    await mcpClient.close();
    console.log("\n👋 Session ended.");
    process.exit(0);
  });
}

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

Conclusion

You've successfully built a Telegram agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback.

Key features of this implementation:

Real-time streaming responses for a better user experience with typewriter effect
Live tool execution feedback showing which tools are being used as the agent works
Dynamic tool loading through Composio's Tool Router with secure authentication
Multi-step tool execution with configurable step limits (up to 10 steps)
Comprehensive error handling for robust agent execution
Conversation history maintenance for context-aware responses

You can extend this further by adding custom error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

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 eligible service messages.

Edit Message

Edit the text of a message identified by chat and message ID or inline message ID.

Forward Message

Forward a message from one chat to another.

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 chat administrators, excluding other bots.

Get Chat History

Poll pending bot updates and filter the returned batch by chat ID or username; this is not complete chat history, and an empty filtered batch does not establish that the chat has no accessible messages.

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, including its ID, name, username and available capability flags.

Get Updates

Receive incoming bot updates using long polling; an outgoing webhook must be removed first, and offsets confirm earlier updates.

Send Document

Send a general file 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 a photo to a Telegram chat using the Bot API.

Send Poll

Send a native poll to a Telegram chat using the Bot API, with a question and answer options.

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

Claude Code

Use Telegram MCP with Claude Code

Cursor

Use Telegram MCP with Cursor

ChatGPT

Use Telegram MCP with ChatGPT

Claude Cowork

Use Telegram MCP with Claude Cowork

Antigravity

Use Telegram MCP with Antigravity

OpenAI Agents SDK

Use Telegram MCP with OpenAI Agents SDK

Claude Agent SDK

Use Telegram MCP with Claude Agent SDK

Grok Bot

Use Telegram MCP with Grok Bot

Codex

Use Telegram MCP with Codex

Kimi Code

Use Telegram MCP with Kimi Code

Grok Build

Use Telegram MCP with Grok Build

VS Code

Use Telegram MCP with VS Code

OpenCode

Use Telegram MCP with OpenCode

OpenClaw

Use Telegram MCP with OpenClaw

Hermes

Use Telegram MCP with Hermes

Atomic Agent

Use Telegram MCP with Atomic Agent

Pi

Use Telegram MCP with Pi

DeepSeek Harness

Use Telegram MCP with DeepSeek Harness

CLI

Use Telegram MCP with CLI

Google ADK

Use Telegram MCP with Google ADK

LangChain

Use Telegram MCP with LangChain

Mastra AI

Use Telegram MCP with Mastra AI

LlamaIndex

Use Telegram MCP with LlamaIndex

CrewAI

Use Telegram MCP with CrewAI

Pydantic AI

Use Telegram MCP with Pydantic AI

AutoGen

Use Telegram MCP with AutoGen

MORE TOOLKITS

Explore Other Toolkits

Toolkit marketplace

Gmail

Oauth2

Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable.

Outlook

Oauth2S2s Oauth2

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

Oauth2

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

BasicOauth2

Gong is a platform for video meetings, call recording, and team collaboration. It helps teams capture conversations, analyze calls, and turn insights into action.

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. Vercel AI SDK v6 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.

Start with Telegram.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Telegram tool your agent needs.Free to start.

Start building

How to integrate Telegram MCP with Vercel AI SDK v6

Connect Telegram without auth hassles

Introduction

Also integrate Telegram with

TL;DR

What is Vercel AI SDK?

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

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

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install required dependencies

Set up environment variables

Import required modules and validate environment

Create Tool Router session and initialize MCP client

Connect to MCP server and retrieve tools

Initialize conversation and CLI interface

Handle user input and stream responses with real-time tool feedback

Complete Code

Conclusion

Supported Tools

How to build Telegram MCP Agent with another framework

Claude Code

Cursor

ChatGPT

Claude Cowork

Antigravity

OpenAI Agents SDK

Claude Agent SDK

Grok Bot

Codex

Kimi Code

Grok Build

VS Code

OpenCode

OpenClaw

Hermes

Atomic Agent

Pi

DeepSeek Harness

CLI

Google ADK

LangChain

Mastra AI

LlamaIndex

CrewAI

Pydantic AI

AutoGen

Explore Other Toolkits

Gmail

Outlook

Slack

Gong

Frequently asked questions

What are the differences in Tool Router MCP and Telegram MCP?+

Can I use Tool Router MCP with Vercel AI SDK v6?+

Can I manage the permissions and scopes for Telegram while using Tool Router?+

How safe is my data with Composio Tool Router?+

Start with Telegram.It takes 30 seconds.