How to integrate DeployHQ MCP with CrewAI

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Introduction

This guide walks you through connecting DeployHQ to CrewAI 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 CrewAI 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 a Composio API key and configure your DeployHQ connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for DeployHQ
  • Build a conversational loop where your agent can execute DeployHQ operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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:
  • Python 3.9 or higher
  • A Composio account and API key
  • A DeployHQ connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

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 crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to DeployHQ via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env

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_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived DeployHQ MCP URL

Create a Composio Tool Router session for DeployHQ

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["deployhq"])

url = session.mcp.url
What's happening:
  • You create a DeployHQ only session through Composio
  • Composio returns an MCP HTTP URL that exposes DeployHQ tools

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's Happening:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

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

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["deployhq"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to DeployHQ through Composio's Tool Router. The agent can perform DeployHQ operations through natural language commands.

Next steps:

  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

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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 CrewAI?

Yes, you can. CrewAI 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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