# How to integrate Maintainx MCP with Autogen ```json { "title": "How to integrate Maintainx MCP with Autogen", "toolkit": "Maintainx", "toolkit_slug": "maintainx", "framework": "AutoGen", "framework_slug": "autogen", "url": "https://composio.dev/toolkits/maintainx/framework/autogen", "markdown_url": "https://composio.dev/toolkits/maintainx/framework/autogen.md", "updated_at": "2026-05-06T08:19:33.009Z" } ``` ## Introduction This guide walks you through connecting Maintainx to AutoGen 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 AutoGen 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) - [LangChain](https://composio.dev/toolkits/maintainx/framework/langchain) - [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 - Install the required dependencies for Autogen and Composio - Initialize Composio and create a Tool Router session for Maintainx - Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams - Configure an Autogen AssistantAgent that can call Maintainx tools - Run a live chat loop where you ask the agent to perform Maintainx operations ## What is AutoGen? Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows. Key features include: - Multi-Agent Systems: Build collaborative agent workflows - MCP Workbench: Native support for Model Context Protocol tools - Streaming HTTP: Connect to external services through streamable HTTP - AssistantAgent: Pre-built agent class for tool-using assistants ## 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 agents and assistants directly to Maintainx. Instead of manually wiring Maintainx APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely. 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 You will need: - A Composio API key - An OpenAI API key (used by Autogen's OpenAIChatCompletionClient) - A Maintainx account you can connect to Composio - Some basic familiarity with Autogen and Python async ### 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 Install Composio, Autogen extensions, and dotenv. What's happening: - composio connects your agent to Maintainx via MCP - autogen-agentchat provides the AssistantAgent class - autogen-ext-openai provides the OpenAI model client - autogen-ext-tools provides MCP workbench support ```bash pip install composio python-dotenv pip install autogen-agentchat autogen-ext-openai autogen-ext-tools ``` ### 3. Set up environment variables Create a .env file in your project folder. What's happening: - COMPOSIO_API_KEY is required to talk to Composio - OPENAI_API_KEY is used by Autogen's OpenAI client - USER_ID is how Composio identifies which user's Maintainx connections to use ```bash COMPOSIO_API_KEY=your-composio-api-key OPENAI_API_KEY=your-openai-api-key USER_ID=your-user-identifier@example.com ``` ### 4. Import dependencies and create Tool Router session What's happening: - load_dotenv() reads your .env file - Composio(api_key=...) initializes the SDK - create(...) creates a Tool Router session that exposes Maintainx tools - session.mcp.url is the MCP endpoint that Autogen will connect to ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from autogen_agentchat.agents import AssistantAgent from autogen_ext.models.openai import OpenAIChatCompletionClient from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams load_dotenv() async def main(): # Initialize Composio and create a Maintainx session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["maintainx"] ) url = session.mcp.url ``` ### 5. Configure MCP parameters for Autogen Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for. What's happening: - url points to the Tool Router MCP endpoint from Composio - timeout is the HTTP timeout for requests - sse_read_timeout controls how long to wait when streaming responses - terminate_on_close=True cleans up the MCP server process when the workbench is closed ```python # Configure MCP server parameters for Streamable HTTP server_params = StreamableHttpServerParams( url=url, timeout=30.0, sse_read_timeout=300.0, terminate_on_close=True, headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")} ) ``` ### 6. Create the model client and agent What's happening: - OpenAIChatCompletionClient wraps the OpenAI model for Autogen - McpWorkbench connects the agent to the MCP tools - AssistantAgent is configured with the Maintainx tools from the workbench ```python # Create model client model_client = OpenAIChatCompletionClient( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY") ) # Use McpWorkbench as context manager async with McpWorkbench(server_params) as workbench: # Create Maintainx assistant agent with MCP tools agent = AssistantAgent( name="maintainx_assistant", description="An AI assistant that helps with Maintainx operations.", model_client=model_client, workbench=workbench, model_client_stream=True, max_tool_iterations=10 ) ``` ### 7. Run the interactive chat loop What's happening: - The script prompts you in a loop with You: - Autogen passes your input to the model, which decides which Maintainx tools to call via MCP - agent.run_stream(...) yields streaming messages as the agent thinks and calls tools - Typing exit, quit, or bye ends the loop ```python print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Maintainx related question or task to the agent.\n") # Conversation loop 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") # Run the agent with streaming try: response_text = "" async for message in agent.run_stream(task=user_input): if hasattr(message, "content") and message.content: response_text = message.content # Print the final response if response_text: print(f"Agent: {response_text}\n") else: print("Agent: I encountered an issue processing your request.\n") except Exception as e: print(f"Agent: Sorry, I encountered an error: {str(e)}\n") ``` ## Complete Code ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from autogen_agentchat.agents import AssistantAgent from autogen_ext.models.openai import OpenAIChatCompletionClient from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams load_dotenv() async def main(): # Initialize Composio and create a Maintainx session composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) session = composio.create( user_id=os.getenv("USER_ID"), toolkits=["maintainx"] ) url = session.mcp.url # Configure MCP server parameters for Streamable HTTP server_params = StreamableHttpServerParams( url=url, timeout=30.0, sse_read_timeout=300.0, terminate_on_close=True, headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")} ) # Create model client model_client = OpenAIChatCompletionClient( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY") ) # Use McpWorkbench as context manager async with McpWorkbench(server_params) as workbench: # Create Maintainx assistant agent with MCP tools agent = AssistantAgent( name="maintainx_assistant", description="An AI assistant that helps with Maintainx operations.", model_client=model_client, workbench=workbench, model_client_stream=True, max_tool_iterations=10 ) print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Maintainx related question or task to the agent.\n") # Conversation loop 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") # Run the agent with streaming try: response_text = "" async for message in agent.run_stream(task=user_input): if hasattr(message, 'content') and message.content: response_text = message.content # Print the final response if response_text: print(f"Agent: {response_text}\n") else: print("Agent: I encountered an issue processing your request.\n") except Exception as e: print(f"Agent: Sorry, I encountered an error: {str(e)}\n") if __name__ == "__main__": asyncio.run(main()) ``` ## Conclusion You now have an Autogen assistant wired into Maintainx through Composio's Tool Router and MCP. From here you can: - Add more toolkits to the toolkits list, for example notion or hubspot - Refine the agent description to point it at specific workflows - Wrap this script behind a UI, Slack bot, or internal tool Once the pattern is clear for Maintainx, you can reuse the same structure for other MCP-enabled apps with minimal code changes. ## 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) - [LangChain](https://composio.dev/toolkits/maintainx/framework/langchain) - [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) ## Related Toolkits - [Apilio](https://composio.dev/toolkits/apilio) - Apilio is a home automation platform that lets you connect and control smart devices from different brands. 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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 Autogen? Yes, you can. Autogen 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)