How to integrate DeployHQ MCP with Autogen

GET STARTED FOR FREE
Framework Integration Gradient
DeployHQ Logo
AutoGen Logo
divider

Introduction

This guide walks you through connecting DeployHQ to AutoGen using the Composio tool router. By the end, you'll have a working DeployHQ agent that can trigger a deployment for project x, list all deployments for project y, get status of last deployment through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a DeployHQ account through Composio's DeployHQ 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:
  • 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 DeployHQ
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call DeployHQ tools
  • Run a live chat loop where you ask the agent to perform DeployHQ 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 DeployHQ MCP server, and what's possible with it?

The DeployHQ MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your DeployHQ account. It provides structured and secure access so your agent can perform DeployHQ operations on your behalf.

Supported Tools & Triggers

Tools
Delete CommandTool to delete a command from a specified project.
Delete ProjectTool to delete a project from DeployHQ.
Delete Build Cache FileTool to delete an existing build cache file from a project.
Delete Excluded File RuleTool to delete an existing excluded file rule from a project.
Delete Server GroupTool to delete a server group from a project using the DeployHQ API.
Delete TemplateTool to delete a template by its unique permalink.
Get ProjectsTool to retrieve all projects from DeployHQ account.
Get ProjectTool to view an existing project in DeployHQ.
Get Project Build Known HostsTool to list all known hosts within a project using DeployHQ API.
Get Project CommandsTool to retrieve all SSH commands configured for a project.
Get Project Config FilesTool to retrieve a list of all config files in a DeployHQ project.
Get Project DeploymentsTool to retrieve a paginated list of all deployments in a project.
Get Project Excluded FilesTool to list all excluded files within a project template.
Get Config FileTool to view a specific config file in a DeployHQ project.
Get Excluded FileTool to view a specific excluded file in a DeployHQ project.
Get Server GroupTool to view a specific server group in a DeployHQ project.
Get Project RepositoryTool to view repository details for a specific project in DeployHQ.
Get Repository BranchesTool to view all available branches in the connected repository for a project.
Get Repository Commit InfoTool to view detailed information about a specific revision in a project's connected repository.
Get Latest Repository RevisionTool to view the latest remote revision of your repository.
Get Recent Commits and TagsTool to view up to 15 most recent revisions and up to 15 most recent tags in a specific branch.
Get Project Scheduled DeploymentsTool to retrieve all upcoming scheduled deployments for a project.
Get Project Server GroupsTool to retrieve all server groups configured for a project.
Get Project ServersTool to retrieve all servers configured for a project.
Get TemplatesTool to retrieve all templates from DeployHQ account.
Get Public TemplateTool to retrieve a specific public template from DeployHQ.
Get Public TemplatesTool to retrieve publicly available deployment templates from DeployHQ.
Update ProjectTool to update project settings in DeployHQ.
Update Build Cache FileTool to update an existing build cache file in a project.
Update Build CommandTool to update an existing build command in a project.
Update Language VersionTool to update the version of a language in a project's build environment.
Update Project CommandTool to update an existing SSH command in a project.
Update Config FileTool to update an existing config file in a DeployHQ project.
Update Excluded FileTool to update an existing excluded file rule in a project.
Update Project RepositoryTool to update repository configuration for a project in DeployHQ.
Update Server GroupTool to update an existing server group in a DeployHQ project.
Update TemplateTool to update an existing template in DeployHQ.
Create ProjectTool to create a new project in DeployHQ.
Generate AI Deployment OverviewTool to generate an AI-powered deployment overview for a revision range.
Create Build Cache FileTool to create a new build cached file within a project.
Create Build CommandTool to create a new build command for a project in DeployHQ.
Create Project Build Known HostTool to create a new known host in a project using DeployHQ API.
Create SSH CommandTool to create a new SSH command for a project in DeployHQ.
Create Config FileTool to create a new config file in a DeployHQ project.
Create Config File DeploymentTool to create a new config file deployment for a project.
Create Excluded FileTool to add a new excluded file to a project.
Abort DeploymentTool to abort a currently running deployment.
Add Project RepositoryTool to add repository details to a project in DeployHQ.
Create Server GroupTool to create a new server group for automated deployments in a DeployHQ project.
Create ServerTool to create a new server configuration in a DeployHQ project.
Create TemplateTool to create a new template in DeployHQ.
Update Project SettingsTool to update settings of an existing DeployHQ project.
Edit Build Cache FileTool to edit an existing build cache file within a project.
Edit Build CommandTool to edit an existing build command within a template in DeployHQ.
Edit SSH CommandTool to edit an existing SSH command in a DeployHQ project.
Edit Config FileTool to edit an existing config file within a project.
Edit Excluded FileTool to edit an existing excluded file rule within a project.
Update Excluded FileTool to update an existing excluded file rule in a project.
Update Project RepositoryTool to update repository details for an existing project in DeployHQ.
Update Server GroupTool to update a server group in a DeployHQ project using the API.
Edit TemplateTool to edit an existing template in DeployHQ.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router 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

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A DeployHQ account you can connect to Composio
  • Some basic familiarity with Autogen and Python async

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 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 DeployHQ via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

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 DeployHQ connections to use

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 DeployHQ session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["deployhq"]
    )
    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 DeployHQ tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to

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

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 DeployHQ assistant agent with MCP tools
    agent = AssistantAgent(
        name="deployhq_assistant",
        description="An AI assistant that helps with DeployHQ 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 DeployHQ tools from the workbench

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any DeployHQ 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 DeployHQ 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 DeployHQ 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 DeployHQ session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["deployhq"]
    )
    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 DeployHQ assistant agent with MCP tools
        agent = AssistantAgent(
            name="deployhq_assistant",
            description="An AI assistant that helps with DeployHQ 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 DeployHQ 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 DeployHQ 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 DeployHQ, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

How to build DeployHQ MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use DeployHQ MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use DeployHQ MCP with Claude Agent SDK

Google ADK

Google ADK

Use DeployHQ MCP with Google ADK

LangChain

LangChain

Use DeployHQ MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use DeployHQ MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use DeployHQ MCP with Mastra AI

LlamaIndex

LlamaIndex

Use DeployHQ MCP with LlamaIndex

CrewAI

CrewAI

Use DeployHQ MCP with CrewAI

Claude Code

Claude Code

Use DeployHQ MCP with Claude Code

Codex

Codex

Use DeployHQ MCP with Codex

FAQ

What are the differences in Tool Router MCP and DeployHQ MCP?

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

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

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

Used by agents from

Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.

Book a call↗Get started for free