How to integrate DeployHQ MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting DeployHQ to the OpenAI Agents SDK 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 OpenAI Agents SDK 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 necessary dependencies
  • Initialize Composio and create a Tool Router session for DeployHQ
  • Configure an AI agent that can use DeployHQ as a tool
  • Run a live chat session where you can ask the agent to perform DeployHQ operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live DeployHQ project
  • Some knowledge of Python or Typescript

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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like DeployHQ.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a DeployHQ Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["deployhq"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only deployhq.
  • The router checks the user's DeployHQ connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access DeployHQ.
  • This approach keeps things lightweight and lets the agent request DeployHQ tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access DeployHQ. "
        "Help users perform DeployHQ operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access DeployHQ and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute DeployHQ operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize DeployHQ.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with DeployHQ and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["deployhq"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access DeployHQ. "
        "Help users perform DeployHQ operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating DeployHQ MCP with OpenAI Agents SDK to build a functional AI agent that can interact with DeployHQ.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

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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 OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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.

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