How to integrate Conductor MCP with Autogen

This guide walks you through connecting Conductor to AutoGen using the Composio tool router. By the end, you'll have a working Conductor agent that can create a workspace for bug triage, start a coding agent refactor session, search transcripts for failed deploy discussion through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Conductor account through Composio's Conductor MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Conductor is a cloud development platform for workspaces, coding-agent sessions, messages, and transcript search. It helps teams run, review, and coordinate agent-driven development in one place.

17 Tools

Introduction

This guide walks you through connecting Conductor to AutoGen using the Composio tool router. By the end, you'll have a working Conductor agent that can create a workspace for bug triage, start a coding agent refactor session, search transcripts for failed deploy discussion through natural language commands.

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

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

Also integrate Conductor with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

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 Conductor
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Conductor tools
  • Run a live chat loop where you ask the agent to perform Conductor 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 Conductor MCP server, and what's possible with it?

The Conductor MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Conductor account. It provides structured and secure access to your projects, cloud workspaces, coding-agent sessions, messages, and transcripts, so your agent can create workspaces, run sessions, exchange messages, manage workspace states, and search transcripts on your behalf.

  • Cloud workspace management: Have your agent create workspaces for available projects, check their status, rename them, or put them to sleep or archive them.
  • Coding-agent session control: Let the agent create and rename sessions, check whether they are idle, working, or in an error state, and stop current work or archive sessions.
  • Agent messaging: Direct your agent to send coding prompts to a session and read individual messages or full session conversations.
  • Transcript search and review: Instruct your agent to search session transcripts with read-only queries and find relevant details from past coding work.
  • Project and activity discovery: Have your agent list available repository projects, browse their workspaces and sessions, and review recent activity.

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

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Conductor account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
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 python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Conductor via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

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 Conductor connections to use
5

Import dependencies and create Tool Router session

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 Conductor session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["conductor"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Conductor tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

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")}
)

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
7

Create the model client and agent

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 Conductor assistant agent with MCP tools
    agent = AssistantAgent(
        name="conductor_assistant",
        description="An AI assistant that helps with Conductor operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Conductor tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Conductor 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")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Conductor 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

Complete Code

Here's the complete code to get you started with Conductor and AutoGen:

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 Conductor session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["conductor"]
    )
    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 Conductor assistant agent with MCP tools
        agent = AssistantAgent(
            name="conductor_assistant",
            description="An AI assistant that helps with Conductor 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 Conductor 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 Conductor 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 Conductor, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

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

Change Workspace State

Put a workspace to sleep or archive it.

Create Session

Create another agent chat session in an existing workspace.

Create Workspace

Create a cloud workspace and its first agent session.

Get Current User

Return the user and organization represented by the connected Conductor API key.

Get Message

Get one transcript message by id.

Get Project

Get one Conductor project and its repository remote by project id.

Get Session

Get one agent session's configuration and current idle, working, or error status in one read.

Get Workspace

Get a workspace's metadata and current lifecycle status in one read, including initialization progress or errors.

List Messages

Read one page of a session transcript or incrementally read messages after a known message ID.

List Projects

List repositories available to the connected account for creating Conductor workspaces.

List Sessions

List one page of agent chat sessions in a Conductor workspace.

List Workspaces

List one page of workspaces belonging to a Conductor project, including deep links and recent activity.

Query Transcripts

Run one read-only SQL SELECT against the organization's session_transcripts_view.

Rename Session

Change an existing Conductor session's display name without stopping its agent.

Rename Workspace

Change the display name of an existing Conductor workspace without changing its lifecycle state.

Send Message

Send a prompt to a Conductor session agent.

Stop Session

Cancel only the current turn and queued messages, or archive the entire session.

FRAMEWORKS

How to build Conductor MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Conductor MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Conductor MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Conductor MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Conductor MCP with Claude Cowork

Codex logo

Codex

Use Conductor MCP with Codex

OpenClaw logo

OpenClaw

Use Conductor MCP with OpenClaw

Hermes logo

Hermes

Use Conductor MCP with Hermes

CLI logo

CLI

Use Conductor MCP with CLI

Google ADK logo

Google ADK

Use Conductor MCP with Google ADK

LangChain logo

LangChain

Use Conductor MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Conductor MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Conductor MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Conductor MCP with LlamaIndex

CrewAI logo

CrewAI

Use Conductor MCP with CrewAI

FAQ

Frequently asked questions

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

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 Conductor tools.

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

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