# How to integrate Maintainx MCP with Pydantic AI ```json { "title": "How to integrate Maintainx MCP with Pydantic AI", "toolkit": "Maintainx", "toolkit_slug": "maintainx", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/maintainx/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/maintainx/framework/pydantic-ai.md", "updated_at": "2026-05-06T08:19:33.009Z" } ``` ## Introduction This guide walks you through connecting Maintainx to Pydantic AI 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 Pydantic AI 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: - How to set up your Composio API key and User ID - How to create a Composio Tool Router session for Maintainx - How to attach an MCP Server to a Pydantic AI agent - How to stream responses and maintain chat history - How to build a simple REPL-style chat interface to test your Maintainx workflows ## What is Pydantic AI? Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications. Key features include: - Type Safety: Built on Pydantic for automatic data validation - MCP Support: Native support for Model Context Protocol servers - Streaming: Built-in support for streaming responses - Async First: Designed for async/await patterns ## 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 Before starting, make sure you have: - Python 3.9 or higher - A Composio account with an active API key - Basic familiarity with Python and async programming ### 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 the required libraries. What's happening: - composio connects your agent to external SaaS tools like Maintainx - pydantic-ai lets you create structured AI agents with tool support - python-dotenv loads your environment variables securely from a .env file ```bash pip install composio pydantic-ai python-dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates your agent to Composio's API - USER_ID associates your session with your account for secure tool access - OPENAI_API_KEY to access OpenAI LLMs ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key ``` ### 4. Import dependencies What's happening: - We load environment variables and import required modules - Composio manages connections to Maintainx - MCPServerStreamableHTTP connects to the Maintainx MCP server endpoint - Agent from Pydantic AI lets you define and run the AI assistant ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStreamableHTTP load_dotenv() ``` ### 5. 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 ```python async def main(): api_key = os.getenv("COMPOSIO_API_KEY") user_id = os.getenv("USER_ID") if not api_key or not user_id: raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment") # Create a Composio Tool Router session for Maintainx composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["maintainx"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") ``` ### 6. Initialize the Pydantic AI Agent What's happening: - The MCP client connects to the Maintainx endpoint - The agent uses GPT-5 to interpret user commands and perform Maintainx operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent maintainx_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[maintainx_mcp], instructions=( "You are a Maintainx assistant. Use Maintainx tools to help users " "with their requests. Ask clarifying questions when needed." ), ) ``` ### 7. Build the chat interface What's happening: - The agent reads input from the terminal and streams its response - Maintainx API calls happen automatically under the hood - The model keeps conversation history to maintain context across turns ```python # Simple REPL with message history history = [] print("Chat started! Type 'exit' or 'quit' to end.\n") print("Try asking the agent to help you with Maintainx.\n") 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", flush=True) async with agent.run_stream(user_input, message_history=history) as stream_result: collected_text = "" async for chunk in stream_result.stream_output(): text_piece = None if isinstance(chunk, str): text_piece = chunk elif hasattr(chunk, "delta") and isinstance(chunk.delta, str): text_piece = chunk.delta elif hasattr(chunk, "text"): text_piece = chunk.text if text_piece: collected_text += text_piece result = stream_result print(f"Agent: {collected_text}\n") history = result.all_messages() ``` ### 8. Run the application What's happening: - The asyncio loop launches the agent and keeps it running until you exit ```python if __name__ == "__main__": asyncio.run(main()) ``` ## Complete Code ```python import asyncio import os from dotenv import load_dotenv from composio import Composio from pydantic_ai import Agent from pydantic_ai.mcp import MCPServerStreamableHTTP load_dotenv() async def main(): api_key = os.getenv("COMPOSIO_API_KEY") user_id = os.getenv("USER_ID") if not api_key or not user_id: raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment") # Create a Composio Tool Router session for Maintainx composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["maintainx"], ) url = session.mcp.url if not url: raise ValueError("Composio session did not return an MCP URL") # Attach the MCP server to a Pydantic AI Agent maintainx_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[maintainx_mcp], instructions=( "You are a Maintainx assistant. Use Maintainx tools to help users " "with their requests. Ask clarifying questions when needed." ), ) # Simple REPL with message history history = [] print("Chat started! Type 'exit' or 'quit' to end.\n") print("Try asking the agent to help you with Maintainx.\n") 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", flush=True) async with agent.run_stream(user_input, message_history=history) as stream_result: collected_text = "" async for chunk in stream_result.stream_output(): text_piece = None if isinstance(chunk, str): text_piece = chunk elif hasattr(chunk, "delta") and isinstance(chunk.delta, str): text_piece = chunk.delta elif hasattr(chunk, "text"): text_piece = chunk.text if text_piece: collected_text += text_piece result = stream_result print(f"Agent: {collected_text}\n") history = result.all_messages() if __name__ == "__main__": asyncio.run(main()) ``` ## Conclusion You've built a Pydantic AI agent that can interact with Maintainx through Composio's Tool Router. With this setup, your agent can perform real Maintainx actions through natural language. You can extend this further by: - Adding other toolkits like Gmail, HubSpot, or Salesforce - Building a web-based chat interface around this agent - Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Maintainx for workflow automation) This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations. ## 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 Pydantic AI? Yes, you can. Pydantic AI 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)