# How to integrate U301 MCP with Autogen

```json
{
  "title": "How to integrate U301 MCP with Autogen",
  "toolkit": "U301",
  "toolkit_slug": "u301",
  "framework": "AutoGen",
  "framework_slug": "autogen",
  "url": "https://composio.dev/toolkits/u301/framework/autogen",
  "markdown_url": "https://composio.dev/toolkits/u301/framework/autogen.md",
  "updated_at": "2026-05-12T10:29:25.636Z"
}
```

## Introduction

This guide walks you through connecting U301 to AutoGen using the Composio tool router. By the end, you'll have a working U301 agent that can shorten this google docs link for sharing, generate a compact url for your event page, create a short link for this product listing through natural language commands.
This guide will help you understand how to give your AutoGen agent real control over a U301 account through Composio's U301 MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate U301 with

- [OpenAI Agents SDK](https://composio.dev/toolkits/u301/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/u301/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/u301/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/u301/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/u301/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/u301/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/u301/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/u301/framework/cli)
- [Google ADK](https://composio.dev/toolkits/u301/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/u301/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/u301/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/u301/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/u301/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/u301/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 U301
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call U301 tools
- Run a live chat loop where you ask the agent to perform U301 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 U301 MCP server, and what's possible with it?

The U301 MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your U301 account. It provides structured and secure access to your U301 resources, so your agent can perform actions like shortening long URLs and managing your shareable links quickly and safely.
- Instant URL shortening: Easily instruct your agent to convert any long web address into a compact, shareable short link with just a prompt.
- Centralized link management: Keep track of the URLs you've shortened and ensure all your important links are organized in one place.
- Seamless sharing workflows: Enable your AI agent to generate short links on demand, making it simple to share resources across chat, email, or documents.
- Consistent branding and access: Use your U301 account to maintain branding and access control over all generated short links.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `U301_DELETE_LINK` | Delete a shortened link | Tool to delete a shortened link by its link identifier. Use when you need to remove a shortened link from the system. |
| `U301_LIST_SHORTEN_DOMAINS` | List available domains for URL shortening | Tool to list available domains for URL shortening, including public domains and custom domains. Use when you need to see what domains are available for creating short links. Supports pagination and filtering by visibility type. |
| `U301_SHORTEN_LINK` | Shorten a long URL | Tool to shorten a long URL into a compact short link. Use after obtaining the long URL when you need a shareable link. |

## Supported Triggers

None listed.

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

The U301 MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to U301. Instead of manually wiring U301 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 U301 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 U301 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 U301 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 U301 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 U301 session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["u301"]
    )
    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 U301 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 U301 assistant agent with MCP tools
    agent = AssistantAgent(
        name="u301_assistant",
        description="An AI assistant that helps with U301 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 U301 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 U301 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 U301 session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["u301"]
    )
    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 U301 assistant agent with MCP tools
        agent = AssistantAgent(
            name="u301_assistant",
            description="An AI assistant that helps with U301 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 U301 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 U301 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 U301, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

## How to build U301 MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/u301/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/u301/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/u301/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/u301/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/u301/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/u301/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/u301/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/u301/framework/cli)
- [Google ADK](https://composio.dev/toolkits/u301/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/u301/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/u301/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/u301/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/u301/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/u301/framework/crew-ai)

## Related Toolkits

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- [Appdrag](https://composio.dev/toolkits/appdrag) - Appdrag is a cloud platform for building websites, APIs, and databases with drag-and-drop tools and code editing. It accelerates development and iteration by combining hosting, database management, and low-code features in one place.
- [Appveyor](https://composio.dev/toolkits/appveyor) - AppVeyor is a cloud-based continuous integration service for building, testing, and deploying applications. It helps developers automate and streamline their software delivery pipelines.
- [Backendless](https://composio.dev/toolkits/backendless) - Backendless is a backend-as-a-service platform for mobile and web apps, offering database, file storage, user authentication, and APIs. It helps developers ship scalable applications faster without managing server infrastructure.
- [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code.
- [Bench](https://composio.dev/toolkits/bench) - Bench is a benchmarking tool for automated performance measurement and analysis. It helps you quickly evaluate, compare, and track your systems or workflows.
- [Better stack](https://composio.dev/toolkits/better_stack) - Better Stack is a monitoring, logging, and incident management solution for apps and services. It helps teams ensure application reliability and performance with real-time insights.
- [Bitbucket](https://composio.dev/toolkits/bitbucket) - Bitbucket is a Git-based code hosting and collaboration platform for teams. It enables secure repository management and streamlined code reviews.
- [Blazemeter](https://composio.dev/toolkits/blazemeter) - Blazemeter is a continuous testing platform for web and mobile app performance. It empowers teams to automate and analyze large-scale tests with ease.
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## Frequently Asked Questions

### What are the differences in Tool Router MCP and U301 MCP?

With a standalone U301 MCP server, the agents and LLMs can only access a fixed set of U301 tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from U301 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 U301 tools.

### Can I manage the permissions and scopes for U301 while using Tool Router?

Yes, absolutely. You can configure which U301 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 U301 data and credentials are handled as safely as possible.

---
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