# How to integrate 2chat MCP with Autogen ```json { "title": "How to integrate 2chat MCP with Autogen", "toolkit": "2chat", "toolkit_slug": "_2chat", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/_2chat/framework/autogen", "markdown_url": "https://composio.dev/toolkits/_2chat/framework/autogen.md", "updated_at": "2026-05-12T09:59:48.591Z" } ``` ## Introduction This guide walks you through connecting 2chat to AutoGen using the Composio tool router. By the end, you'll have a working 2chat agent that can add new whatsapp contact for sales lead, list all whatsapp contacts and their details, check your 2chat api usage this week through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a 2chat account through Composio's 2chat MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate 2chat with - [OpenAI Agents SDK](https://composio.dev/toolkits/_2chat/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/_2chat/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/_2chat/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/_2chat/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/_2chat/framework/codex) - [OpenClaw](https://composio.dev/toolkits/_2chat/framework/openclaw) - [Hermes](https://composio.dev/toolkits/_2chat/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/_2chat/framework/cli) - [Google ADK](https://composio.dev/toolkits/_2chat/framework/google-adk) - [LangChain](https://composio.dev/toolkits/_2chat/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/_2chat/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/_2chat/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/_2chat/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/_2chat/framework/crew-ai) ## TL;DR Here's what you'll learn: - Get and set up your OpenAI and Composio API keys - Install the required dependencies for Autogen and Composio - Initialize Composio and create a Tool Router session for 2chat - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call 2chat tools - Run a live chat loop where you ask the agent to perform 2chat operations ## What is AutoGen? Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows. Key features include: - Multi-Agent Systems: Build collaborative agent workflows - MCP Workbench: Native support for Model Context Protocol tools - Streaming HTTP: Connect to external services through streamable HTTP - AssistantAgent: Pre-built agent class for tool-using assistants ## What is the 2chat MCP server, and what's possible with it? The 2chat MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your 2chat account. It provides structured and secure access to your messaging channels, so your agent can perform actions like sending and receiving WhatsApp messages, managing contacts, monitoring API usage, and automating group workflows on your behalf. - Contact management and automation: Quickly add new contacts or retrieve existing ones, allowing your agent to keep your WhatsApp and text channels up to date and organized. - API usage monitoring: Effortlessly check your current API usage and quotas, so your agent can help prevent service interruptions or overages. - Webhook subscription review: Let your agent list and audit all active webhook subscriptions for your messaging channels, making it easy to monitor integrations and event triggers. - Credential validation and account status: Have your agent validate API keys and fetch account information to ensure secure and reliable operation before performing messaging tasks. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `_2CHAT_CREATE_CONTACT` | Create Contact | Tool to create a new contact in your 2Chat account. Use after gathering and verifying first name and at least one contact detail (email, phone, or address). | | `_2CHAT_GET_API_USAGE_INFO` | Get API Usage Info | Tool to retrieve current API usage and account information. Use when you need to monitor your remaining quotas before sending more requests. | | `_2CHAT_LIST_CONTACTS` | List Contacts | Tool to list all contacts in your 2Chat account. Use when you need to retrieve your contact list after confirming your account connection. | | `_2CHAT_LIST_WEBHOOKS` | List Webhook Subscriptions | List all configured webhook subscriptions for WhatsApp and phone call events. Use this when you need to audit, review, or retrieve UUIDs of your active webhook subscriptions. Returns details including webhook UUID, event type, channel UUID, callback URL, and creation timestamp. | | `_2CHAT_TEST_API_KEY` | Test API Key | Tool to validate your API key and retrieve account info. Use when confirming credentials before performing other operations. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The 2chat MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to 2chat. Instead of manually wiring 2chat APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely. 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 You will need: - A Composio API key - An OpenAI API key (used by Autogen's OpenAIChatCompletionClient) - A 2chat account you can connect to Composio - Some basic familiarity with Autogen and Python async ### 1. Getting API Keys for OpenAI and Composio OpenAI API Key - Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider. - Keep the API key safe. Composio API Key - Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install dependencies Install Composio, Autogen extensions, and dotenv. What's happening: - composio connects your agent to 2chat via MCP - autogen-agentchat provides the AssistantAgent class - autogen-ext-openai provides the OpenAI model client - autogen-ext-tools provides MCP workbench support ```bash pip install composio python-dotenv pip install autogen-agentchat autogen-ext-openai autogen-ext-tools ``` ### 3. Set up environment variables Create a .env file in your project folder. What's happening: - COMPOSIO_API_KEY is required to talk to Composio - OPENAI_API_KEY is used by Autogen's OpenAI client - USER_ID is how Composio identifies which user's 2chat connections to use ```bash COMPOSIO_API_KEY=your-composio-api-key OPENAI_API_KEY=your-openai-api-key USER_ID=your-user-identifier@example.com ``` ### 4. Import dependencies and create Tool Router session What's happening: - load_dotenv() reads your .env file - Composio(api_key=...) initializes the SDK - create(...) creates a Tool Router session that exposes 2chat tools - session.mcp.url is the MCP endpoint that Autogen will connect to ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from autogen_agentchat.agents import AssistantAgent from autogen_ext.models.openai import OpenAIChatCompletionClient from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams load_dotenv() async def main(): # Initialize Composio and create a 2chat session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["_2chat"] ) url = session.mcp.url ``` ### 5. Configure MCP parameters for Autogen Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for. What's happening: - url points to the Tool Router MCP endpoint from Composio - timeout is the HTTP timeout for requests - sse_read_timeout controls how long to wait when streaming responses - terminate_on_close=True cleans up the MCP server process when the workbench is closed ```python # Configure MCP server parameters for Streamable HTTP server_params = StreamableHttpServerParams( url=url, timeout=30.0, sse_read_timeout=300.0, terminate_on_close=True, headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")} ) ``` ### 6. Create the model client and agent What's happening: - OpenAIChatCompletionClient wraps the OpenAI model for Autogen - McpWorkbench connects the agent to the MCP tools - AssistantAgent is configured with the 2chat tools from the workbench ```python # Create model client model_client = OpenAIChatCompletionClient( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY") ) # Use McpWorkbench as context manager async with McpWorkbench(server_params) as workbench: # Create 2chat assistant agent with MCP tools agent = AssistantAgent( name="_2chat_assistant", description="An AI assistant that helps with 2chat operations.", model_client=model_client, workbench=workbench, model_client_stream=True, max_tool_iterations=10 ) ``` ### 7. Run the interactive chat loop What's happening: - The script prompts you in a loop with You: - Autogen passes your input to the model, which decides which 2chat tools to call via MCP - agent.run_stream(...) yields streaming messages as the agent thinks and calls tools - Typing exit, quit, or bye ends the loop ```python print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any 2chat related question or task to the agent.\n") # Conversation loop while True: user_input = input("You: ").strip() if user_input.lower() in ["exit", "quit", "bye"]: print("\nGoodbye!") break if not user_input: continue print("\nAgent is thinking...\n") # Run the agent with streaming try: response_text = "" async for message in agent.run_stream(task=user_input): if hasattr(message, "content") and message.content: response_text = message.content # Print the final response if response_text: print(f"Agent: {response_text}\n") else: print("Agent: I encountered an issue processing your request.\n") except Exception as e: print(f"Agent: Sorry, I encountered an error: {str(e)}\n") ``` ## Complete Code ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from autogen_agentchat.agents import AssistantAgent from autogen_ext.models.openai import OpenAIChatCompletionClient from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams load_dotenv() async def main(): # Initialize Composio and create a 2chat session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["_2chat"] ) url = session.mcp.url # Configure MCP server parameters for Streamable HTTP server_params = StreamableHttpServerParams( url=url, timeout=30.0, sse_read_timeout=300.0, terminate_on_close=True, headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")} ) # Create model client model_client = OpenAIChatCompletionClient( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY") ) # Use McpWorkbench as context manager async with McpWorkbench(server_params) as workbench: # Create 2chat assistant agent with MCP tools agent = AssistantAgent( name="_2chat_assistant", description="An AI assistant that helps with 2chat operations.", model_client=model_client, workbench=workbench, model_client_stream=True, max_tool_iterations=10 ) print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any 2chat related question or task to the agent.\n") # Conversation loop while True: user_input = input("You: ").strip() if user_input.lower() in ['exit', 'quit', 'bye']: print("\nGoodbye!") break if not user_input: continue print("\nAgent is thinking...\n") # Run the agent with streaming try: response_text = "" async for message in agent.run_stream(task=user_input): if hasattr(message, 'content') and message.content: response_text = message.content # Print the final response if response_text: print(f"Agent: {response_text}\n") else: print("Agent: I encountered an issue processing your request.\n") except Exception as e: print(f"Agent: Sorry, I encountered an error: {str(e)}\n") if __name__ == "__main__": asyncio.run(main()) ``` ## Conclusion You now have an Autogen assistant wired into 2chat through Composio's Tool Router and MCP. From here you can: - Add more toolkits to the toolkits list, for example notion or hubspot - Refine the agent description to point it at specific workflows - Wrap this script behind a UI, Slack bot, or internal tool Once the pattern is clear for 2chat, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## How to build 2chat MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/_2chat/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/_2chat/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/_2chat/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/_2chat/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/_2chat/framework/codex) - [OpenClaw](https://composio.dev/toolkits/_2chat/framework/openclaw) - [Hermes](https://composio.dev/toolkits/_2chat/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/_2chat/framework/cli) - [Google ADK](https://composio.dev/toolkits/_2chat/framework/google-adk) - [LangChain](https://composio.dev/toolkits/_2chat/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/_2chat/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/_2chat/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/_2chat/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/_2chat/framework/crew-ai) ## Related Toolkits - [Gmail](https://composio.dev/toolkits/gmail) - 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](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. - [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 2chat MCP? With a standalone 2chat MCP server, the agents and LLMs can only access a fixed set of 2chat tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from 2chat and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with Autogen? Yes, you can. Autogen 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 2chat tools. ### Can I manage the permissions and scopes for 2chat while using Tool Router? Yes, absolutely. You can configure which 2chat 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 2chat data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)