How to integrate DeployHQ MCP with Pydantic AI

This guide walks you through connecting DeployHQ to Pydantic AI 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 Pydantic AI 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.

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DeployHQ is a deployment automation service for Git, SVN, and Mercurial projects. It streamlines code deployments, making project launches seamless and reliable.

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Introduction

This guide walks you through connecting DeployHQ to Pydantic AI 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 Pydantic AI 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.

Also integrate DeployHQ with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for DeployHQ
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your DeployHQ workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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.

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 step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like DeployHQ
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to DeployHQ
  • MCPServerStreamableHTTP connects to the DeployHQ MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for DeployHQ
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["deployhq"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to DeployHQ tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
deployhq_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[deployhq_mcp],
    instructions=(
        "You are a DeployHQ assistant. Use DeployHQ tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the DeployHQ endpoint
  • The agent uses GPT-5 to interpret user commands and perform DeployHQ operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with DeployHQ.\n")

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", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • DeployHQ API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with DeployHQ and Pydantic AI:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for DeployHQ
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["deployhq"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    deployhq_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[deployhq_mcp],
        instructions=(
            "You are a DeployHQ assistant. Use DeployHQ tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with DeployHQ.\n")

    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", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with DeployHQ through Composio's Tool Router. With this setup, your agent can perform real DeployHQ actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + DeployHQ for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

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

Delete Command

Tool to delete a command from a specified project.

Delete Project

Tool to delete a project from DeployHQ.

Delete Build Cache File

Tool to delete an existing build cache file from a project.

Delete Excluded File Rule

Tool to delete an existing excluded file rule from a project.

Delete Server Group

Tool to delete a server group from a project using the DeployHQ API.

Delete Template

Tool to delete a template by its unique permalink.

Get Projects

Tool to retrieve all projects from DeployHQ account.

Get Project

Tool to view an existing project in DeployHQ.

Get Project Build Known Hosts

Tool to list all known hosts within a project using DeployHQ API.

Get Project Commands

Tool to retrieve all SSH commands configured for a project.

Get Project Config Files

Tool to retrieve a list of all config files in a DeployHQ project.

Get Project Deployments

Tool to retrieve a paginated list of all deployments in a project.

Get Project Excluded Files

Tool to list all excluded files within a project template.

Get Config File

Tool to view a specific config file in a DeployHQ project.

Get Excluded File

Tool to view a specific excluded file in a DeployHQ project.

Get Server Group

Tool to view a specific server group in a DeployHQ project.

Get Project Repository

Tool to view repository details for a specific project in DeployHQ.

Get Repository Branches

Tool to view all available branches in the connected repository for a project.

Get Repository Commit Info

Tool to view detailed information about a specific revision in a project's connected repository.

Get Latest Repository Revision

Tool to view the latest remote revision of your repository.

Get Recent Commits and Tags

Tool to view up to 15 most recent revisions and up to 15 most recent tags in a specific branch.

Get Project Scheduled Deployments

Tool to retrieve all upcoming scheduled deployments for a project.

Get Project Server Groups

Tool to retrieve all server groups configured for a project.

Get Project Servers

Tool to retrieve all servers configured for a project.

Get Templates

Tool to retrieve all templates from DeployHQ account.

Get Public Template

Tool to retrieve a specific public template from DeployHQ.

Get Public Templates

Tool to retrieve publicly available deployment templates from DeployHQ.

Update Project

Tool to update project settings in DeployHQ.

Update Build Cache File

Tool to update an existing build cache file in a project.

Update Build Command

Tool to update an existing build command in a project.

Update Language Version

Tool to update the version of a language in a project's build environment.

Update Project Command

Tool to update an existing SSH command in a project.

Update Config File

Tool to update an existing config file in a DeployHQ project.

Update Excluded File

Tool to update an existing excluded file rule in a project.

Update Project Repository

Tool to update repository configuration for a project in DeployHQ.

Update Server Group

Tool to update an existing server group in a DeployHQ project.

Update Template

Tool to update an existing template in DeployHQ.

Create Project

Tool to create a new project in DeployHQ.

Generate AI Deployment Overview

Tool to generate an AI-powered deployment overview for a revision range.

Create Build Cache File

Tool to create a new build cached file within a project.

Create Build Command

Tool to create a new build command for a project in DeployHQ.

Create Project Build Known Host

Tool to create a new known host in a project using DeployHQ API.

Create SSH Command

Tool to create a new SSH command for a project in DeployHQ.

Create Config File

Tool to create a new config file in a DeployHQ project.

Create Config File Deployment

Tool to create a new config file deployment for a project.

Create Excluded File

Tool to add a new excluded file to a project.

Abort Deployment

Tool to abort a currently running deployment.

Add Project Repository

Tool to add repository details to a project in DeployHQ.

Create Server Group

Tool to create a new server group for automated deployments in a DeployHQ project.

Create Server

Tool to create a new server configuration in a DeployHQ project.

Create Template

Tool to create a new template in DeployHQ.

Update Project Settings

Tool to update settings of an existing DeployHQ project.

Edit Build Cache File

Tool to edit an existing build cache file within a project.

Edit Build Command

Tool to edit an existing build command within a template in DeployHQ.

Edit SSH Command

Tool to edit an existing SSH command in a DeployHQ project.

Edit Config File

Tool to edit an existing config file within a project.

Edit Excluded File

Tool to edit an existing excluded file rule within a project.

Update Excluded File

Tool to update an existing excluded file rule in a project.

Update Project Repository

Tool to update repository details for an existing project in DeployHQ.

Update Server Group

Tool to update a server group in a DeployHQ project using the API.

Edit Template

Tool to edit an existing template in DeployHQ.

FRAMEWORKS

How to build DeployHQ MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use DeployHQ MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use DeployHQ MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use DeployHQ MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use DeployHQ MCP with Claude Cowork

Codex logo

Codex

Use DeployHQ MCP with Codex

OpenClaw logo

OpenClaw

Use DeployHQ MCP with OpenClaw

Hermes logo

Hermes

Use DeployHQ MCP with Hermes

CLI logo

CLI

Use DeployHQ MCP with CLI

Google ADK logo

Google ADK

Use DeployHQ MCP with Google ADK

LangChain logo

LangChain

Use DeployHQ MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use DeployHQ MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use DeployHQ MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use DeployHQ MCP with LlamaIndex

CrewAI logo

CrewAI

Use DeployHQ MCP with CrewAI

FAQ

Frequently asked questions

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.

Yes, you can. Pydantic AI 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.

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.

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.

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Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

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Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

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