# How to integrate Maintainx MCP with LangChain

```json
{
  "title": "How to integrate Maintainx MCP with LangChain",
  "toolkit": "Maintainx",
  "toolkit_slug": "maintainx",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/maintainx/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/maintainx/framework/langchain.md",
  "updated_at": "2026-05-06T08:19:33.009Z"
}
```

## Introduction

This guide walks you through connecting Maintainx to LangChain using the Composio tool router. By the end, you'll have a working Maintainx agent that can create a new urgent work order for hvac, list all open work orders at warehouse, add comment to work order 12345 through natural language commands.
This guide will help you understand how to give your LangChain agent real control over a Maintainx account through Composio's Maintainx MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Maintainx with

- [OpenAI Agents SDK](https://composio.dev/toolkits/maintainx/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/maintainx/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/maintainx/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/maintainx/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/maintainx/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/maintainx/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/maintainx/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/maintainx/framework/cli)
- [Google ADK](https://composio.dev/toolkits/maintainx/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/maintainx/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/maintainx/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/maintainx/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/maintainx/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Connect your Maintainx project to Composio
- Create a Tool Router MCP session for Maintainx
- Initialize an MCP client and retrieve Maintainx tools
- Build a LangChain agent that can interact with Maintainx
- 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 Maintainx MCP server, and what's possible with it?

The Maintainx MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Maintainx account. It provides structured and secure access to your maintenance operations, so your agent can create work orders, update existing tasks, manage assets, and keep your teams aligned—automatically and on your behalf.
- Work order creation and management: Instantly have your agent create new work orders, add detailed descriptions, set priorities, and assign them to the right teams or users.
- Automated work order updates and comments: Let your agent update existing work orders or add comments for documentation and real-time communication between team members.
- Asset and location tracking: Effortlessly list and retrieve all assets and locations across your organization, helping you keep maintenance data organized and accessible.
- Category and team organization: Enable your agent to fetch and manage categories or teams, ensuring work orders and assets are classified and assigned correctly.
- Smart work request portals: Have your agent generate custom work request portals so stakeholders can submit maintenance requests easily and securely.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `MAINTAINX_CREATE_WORK_ORDER` | Create Work Order | This tool creates a new work order in maintainx. it uses the post /api/v1/workorders endpoint. the tool requires a 'title' for the work order and offers several optional parameters including description, priority, duedate, startdate, userids, teamids, proceduretemplateid, locationid, assetid, and categories. |
| `MAINTAINX_CREATE_WORK_ORDER_COMMENT` | Create Work Order Comment | This tool creates a new comment on an existing work order in maintainx. it allows users to add comments for documentation, updates, or communication purposes within a specific work order. it requires a workorderid and the text content of the comment to create a new comment on the work order, providing capabilities to update maintenance work order records. |
| `MAINTAINX_CREATE_WORK_REQUEST_PORTAL` | Create Work Request Portal | Creates a new work request portal in maintainx. a work request portal allows users to submit work requests through a dedicated url. the portal can be customized with a title, welcome text, and description placeholder. it can be associated with a specific location and asset, and can be configured to require email contact information. |
| `MAINTAINX_FIND_ENTITY` | Find Entity | A tool to search and find specific entities within maintainx by specified fields. this tool allows users to search for different types of entities including work orders, users, and locations. |
| `MAINTAINX_LIST_ASSETS` | List Assets | This tool allows users to retrieve a list of all assets in their organization. |
| `MAINTAINX_LIST_CATEGORIES` | List Categories | This tool retrieves a list of all categories in your maintainx organization. categories are used to organize and classify work orders, assets, and other items in the system. it supports listing the categories with pagination and provides details such as category id, name, description, and timestamps for creation and update. |
| `MAINTAINX_LIST_LOCATIONS` | List Locations | This tool retrieves a list of all available locations in the organization's maintainx account. the locations can be physical places where assets are located, work is performed, or maintenance is needed. |
| `MAINTAINX_LIST_TEAMS` | List Teams | This tool retrieves a list of all teams in your maintainx organization. |
| `MAINTAINX_LIST_WORK_ORDERS` | List Work Orders | Action to list work orders from maintainx. |
| `MAINTAINX_UPDATE_WORK_ORDER` | Update Work Order | This tool allows users to update an existing work order in maintainx by modifying specific attributes without affecting other unchanged fields. it requires the workorder id and at least one of the optional parameters (title, description, or priority) to perform the update. |
| `MAINTAINX_UPDATE_WORK_ORDER_STATUS` | Update Work Order Status | This tool allows users to update the status of a specific work order in maintainx. it is focused specifically on status updates, making it more streamlined than the comprehensive 'update work order' action which allows updating multiple fields. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Maintainx MCP server is an implementation of the Model Context Protocol that connects your AI agent to Maintainx. It provides structured and secure access so your agent can perform Maintainx operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

No description provided.

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

No description provided.
```python
pip install composio-langchain langchain-mcp-adapters langchain python-dotenv
```

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

### 3. Set up environment variables

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
```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
```

### 4. Import dependencies

No description provided.
```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
```

```typescript
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();
```

### 5. Initialize Composio client

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 Maintainx tools
- Validating that COMPOSIO_USER_ID is also set before proceeding
```python
async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
```

```typescript
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()
    });
```

### 6. Create a Tool Router session

What's happening:
- We're creating a Tool Router session that gives your agent access to Maintainx 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 Maintainx tools as needed
```python
# Create Tool Router session for Maintainx
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['maintainx']
)

url = session.mcp.url
```

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

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "maintainx-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
```

```typescript
const client = new MultiServerMCPClient({
    "maintainx-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 });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

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

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

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

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
```

```typescript
let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Maintainx 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);
    });
```

### 9. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(main())
```

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

## Complete Code

```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['maintainx']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "maintainx-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Maintainx related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

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

```typescript
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: ['maintainx']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "maintainx-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 Maintainx 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 Maintainx 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.

## How to build Maintainx MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/maintainx/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/maintainx/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/maintainx/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/maintainx/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/maintainx/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/maintainx/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/maintainx/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/maintainx/framework/cli)
- [Google ADK](https://composio.dev/toolkits/maintainx/framework/google-adk)
- [Vercel AI SDK](https://composio.dev/toolkits/maintainx/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/maintainx/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/maintainx/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/maintainx/framework/crew-ai)

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## Frequently Asked Questions

### What are the differences in Tool Router MCP and Maintainx MCP?

With a standalone Maintainx MCP server, the agents and LLMs can only access a fixed set of Maintainx tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Maintainx and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with LangChain?

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 Maintainx tools.

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

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

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)