# How to integrate Superchat MCP with Autogen

```json
{
  "title": "How to integrate Superchat MCP with Autogen",
  "toolkit": "Superchat",
  "toolkit_slug": "superchat",
  "framework": "AutoGen",
  "framework_slug": "autogen",
  "url": "https://composio.dev/toolkits/superchat/framework/autogen",
  "markdown_url": "https://composio.dev/toolkits/superchat/framework/autogen.md",
  "updated_at": "2026-05-12T10:27:31.364Z"
}
```

## Introduction

This guide walks you through connecting Superchat to AutoGen using the Composio tool router. By the end, you'll have a working Superchat agent that can list all whatsapp conversations from today, create a new contact for incoming lead, fetch details for contact john smith through natural language commands.
This guide will help you understand how to give your AutoGen agent real control over a Superchat account through Composio's Superchat MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Superchat with

- [OpenAI Agents SDK](https://composio.dev/toolkits/superchat/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/superchat/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/superchat/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/superchat/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/superchat/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/superchat/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/superchat/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/superchat/framework/cli)
- [Google ADK](https://composio.dev/toolkits/superchat/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/superchat/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/superchat/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/superchat/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/superchat/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/superchat/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 Superchat
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call Superchat tools
- Run a live chat loop where you ask the agent to perform Superchat 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 Superchat MCP server, and what's possible with it?

The Superchat MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Superchat account. It provides structured and secure access to your unified messaging platform, so your agent can perform actions like managing contacts, listing conversations, organizing templates, and retrieving channel information across messaging channels on your behalf.
- Unified contact management: Easily create, fetch, and list contacts, allowing your agent to manage your customer database and keep your communications up to date.
- Conversation and channel insights: Ask your agent to list all ongoing conversations and available messaging channels, making it easy to monitor activity and streamline engagement across platforms.
- Template and folder organization: Have your agent create new template folders to organize message templates for efficient, consistent communication with customers.
- Custom attribute retrieval: Let your agent pull all custom contact attributes, enabling dynamic personalization and tailored messaging workflows.
- Webhook and file management: Direct your agent to delete obsolete webhooks or retrieve file metadata, keeping your integrations clean and your resources easily accessible.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `SUPERCHAT_CREATE_CONTACT` | Create Contact | Create a new contact in Superchat with phone or email handles. Use this tool to register contact details before sending messages. You must provide at least one handle (phone or email). Optional fields include first name, last name, gender, and custom attributes (if predefined in your account settings). |
| `SUPERCHAT_CREATE_TEMPLATE_FOLDER` | Create Template Folder | Create a new template folder in SuperChat for organizing message templates. Template folders help organize WhatsApp and other messaging templates into logical groups (e.g., Marketing, Sales, Customer Support). Use this action before creating templates when you want to keep them organized. |
| `SUPERCHAT_DELETE_WEBHOOK` | Delete Webhook | Tool to delete a specific webhook by its ID. Use when you need to remove an obsolete or unwanted webhook subscription. First use SUPERCHAT_LIST_WEBHOOKS to retrieve the webhook ID, then use this action to delete it. Example: Delete webhook wh_UPYSN0Etofjl7lhhQ9yhL. |
| `SUPERCHAT_GET_CONTACT` | Get Contact | Retrieve a specific contact's details by ID. Returns the contact's name, handles (phone, email, social), custom attributes, and timestamps. Use this to look up contact information before sending messages or updating contact details. Example: "Get contact details for co_abc123" or "Fetch info for contact co_xyz789". |
| `SUPERCHAT_GET_FILE` | Get File | Retrieve metadata for a specific file by its ID. Returns file details including the file name, MIME type, API resource URL, and a temporary download link with expiration. Use this to get information about uploaded files before downloading or processing them. |
| `SUPERCHAT_GET_USER` | Get User | Retrieve details of a specific user in the Superchat workspace by their user ID. Use this tool when you need to fetch profile information for a known user. Note: You can obtain user IDs by first calling the List Users action. Example user_id format: 'us_abc123xyz' |
| `SUPERCHAT_LIST_CHANNELS` | List Channels | Lists all communication channels in your Superchat workspace. Channels represent different messaging mediums (WhatsApp, email, SMS, Telegram, Instagram, Facebook) through which conversations occur. Results are sorted by creation date (newest first) and can be paginated using 'limit', 'after', or 'before' parameters. |
| `SUPERCHAT_LIST_CONTACTS` | List Contacts | List all contacts in the Superchat workspace with cursor-based pagination. Use this tool to browse contacts, find contact IDs, or export contact data. Results are sorted by creation date (newest first). |
| `SUPERCHAT_LIST_CONVERSATIONS` | List Conversations | Retrieves a paginated list of all conversations in your Superchat account. Each conversation includes channel info, status (open/snoozed/done), assigned users, contacts, labels, and inbox details. Use this to browse conversations, find specific ones by status or channel, or get conversation IDs for further operations. Supports cursor-based pagination to handle large result sets. |
| `SUPERCHAT_LIST_CUSTOM_ATTRIBUTES` | List Custom Attributes | List all custom attributes defined for contacts in your Superchat account. Custom attributes are user-defined fields that extend contact data beyond standard fields like name and email. Use this action to discover available custom attributes before reading or updating contact information. Supports cursor-based pagination for accounts with many custom attributes. Common use cases: - Discover available custom fields before updating contacts - Retrieve custom attribute types (string, number, date, select, etc.) - Get custom attribute IDs for use in other API calls |
| `SUPERCHAT_LIST_INBOXES` | List Inboxes | Tool to list all inboxes. Use when you need to retrieve inbox IDs and metadata before sending or organizing messages. |
| `SUPERCHAT_LIST_LABELS` | List Labels | List all labels in the Superchat workspace. Labels are used to categorize and organize conversations. Use this tool to retrieve available labels and their IDs, which can then be used to assign labels to conversations via the update conversation endpoint. Supports cursor-based pagination for workspaces with many labels. |
| `SUPERCHAT_LIST_TEMPLATES` | List Templates | Tool to list all message templates. Use when you need to fetch available message templates. |
| `SUPERCHAT_LIST_USERS` | List Users | Retrieve all users in the workspace. Returns user profiles including names, emails, roles, and contact info. Supports pagination for large workspaces. Use cases: - Get a directory of all workspace members - Find user IDs for other API operations - Audit user roles and permissions |
| `SUPERCHAT_LIST_WEBHOOKS` | List Webhooks | Tool to list all webhooks configured in the workspace. Use this tool to: - Retrieve all active and paused webhooks - Get webhook IDs for use with update or delete operations - Check webhook status and event subscriptions Supports pagination via 'limit', 'after', and 'before' parameters. |
| `SUPERCHAT_UPDATE_CONTACT` | Update Contact | Update information for a specific contact in Superchat. Use this tool to modify a contact's name, gender, handles (phone/email), or custom attributes. Requires the contact_id (prefixed with 'ct_') which can be obtained from List Contacts or Create Contact. Examples: - Update first name: {"contact_id": "ct_abc123", "first_name": "Jane"} - Update gender: {"contact_id": "ct_abc123", "gender": "female"} - Update phone handle: {"contact_id": "ct_abc123", "handles": [{"type": "phone", "value": "+1234567890"}]} |
| `SUPERCHAT_UPDATE_WEBHOOK` | Update Webhook | Update an existing webhook's target URL and/or event subscriptions. Use this tool to: - Change the webhook delivery URL - Add or remove event subscriptions - Update event types the webhook listens to Note: Webhook status (ACTIVE/PAUSED) is automatically managed by the API and cannot be manually changed. Webhooks become PAUSED after 7 days of consistent delivery failures. |

## Supported Triggers

None listed.

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

The Superchat MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Superchat. Instead of manually wiring Superchat 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 Superchat 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 Superchat 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 Superchat 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 Superchat 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 Superchat session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["superchat"]
    )
    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 Superchat 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 Superchat assistant agent with MCP tools
    agent = AssistantAgent(
        name="superchat_assistant",
        description="An AI assistant that helps with Superchat 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 Superchat 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 Superchat 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 Superchat session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["superchat"]
    )
    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 Superchat assistant agent with MCP tools
        agent = AssistantAgent(
            name="superchat_assistant",
            description="An AI assistant that helps with Superchat 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 Superchat 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 Superchat 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 Superchat, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

## How to build Superchat MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/superchat/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/superchat/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/superchat/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/superchat/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/superchat/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/superchat/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/superchat/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/superchat/framework/cli)
- [Google ADK](https://composio.dev/toolkits/superchat/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/superchat/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/superchat/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/superchat/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/superchat/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/superchat/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.
- [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.

## Frequently Asked Questions

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

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

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

Yes, absolutely. You can configure which Superchat 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 Superchat data and credentials are handled as safely as possible.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)
