How to integrate DeployHQ MCP with LangChain

This guide walks you through connecting DeployHQ to LangChain 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 LangChain 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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Introduction

This guide walks you through connecting DeployHQ to LangChain 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 LangChain 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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TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your DeployHQ project to Composio
  • Create a Tool Router MCP session for DeployHQ
  • Initialize an MCP client and retrieve DeployHQ tools
  • Build a LangChain agent that can interact with DeployHQ
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

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 step10 STEPS
1

Prerequisites

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI 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

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • @composio/langchain provides Composio integration for LangChain
  • @langchain/mcp-adapters enables MCP client connections
  • @langchain/core is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_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 your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models
5

Import dependencies

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv/config import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with DeployHQ functionality through MCP
6

Initialize Composio client

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to DeployHQ tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding
7

Create a Tool Router session

const session = await composio.create(
    userId as string,
    {
        toolkits: ['deployhq']
    }
);

const url = session.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
  • This approach allows the agent to dynamically load and use DeployHQ tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "deployhq-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
What's happening:
  • We're creating a MultiServerMCPClient that connects to our DeployHQ MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available DeployHQ tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model
9

Set up interactive chat interface

let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any DeployHQ related question or task to the agent.\n");

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

rl.prompt();

rl.on('line', async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

    if (!trimmedInput) {
        rl.prompt();
        return;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
What's happening:
  • We initialize an empty conversationHistory list to maintain context across interactions
  • A readline interface is used to continuously accept user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the invoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully
10

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
What's happening:
  • We call the main() function to start the application

Complete Code

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

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['deployhq']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "deployhq-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any DeployHQ related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});

Conclusion

You've successfully built a LangChain agent that can interact with DeployHQ through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.
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.

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. LangChain 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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