# How to integrate Autom MCP with Pydantic AI ```json { "title": "How to integrate Autom MCP with Pydantic AI", "toolkit": "Autom", "toolkit_slug": "autom", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/autom/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/autom/framework/pydantic-ai.md", "updated_at": "2026-05-12T10:02:15.170Z" } ``` ## Introduction This guide walks you through connecting Autom to Pydantic AI using the Composio tool router. By the end, you'll have a working Autom agent that can find top google images for electric cars, list google-supported countries in south america, get language codes for website localization through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Autom account through Composio's Autom MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Autom with - [OpenAI Agents SDK](https://composio.dev/toolkits/autom/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/autom/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/autom/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/autom/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/autom/framework/codex) - [OpenClaw](https://composio.dev/toolkits/autom/framework/openclaw) - [Hermes](https://composio.dev/toolkits/autom/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/autom/framework/cli) - [Google ADK](https://composio.dev/toolkits/autom/framework/google-adk) - [LangChain](https://composio.dev/toolkits/autom/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/autom/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/autom/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/autom/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/autom/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 Autom - 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 Autom 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 Autom MCP server, and what's possible with it? The Autom MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Autom account. It provides structured and secure access to lightning-fast search engine data, so your agent can perform actions like fetching Google images, listing supported countries and languages, and searching for Google locations—all on your behalf. - Instant Google image search: Let your agent fetch image results from Google, including URLs, titles, domains, and relevant metadata for any search query. - Supported country discovery: Ask your agent to list all Google-supported countries or filter them to suggest the most relevant locations for your needs. - Language code retrieval: Retrieve a comprehensive list of Google-supported language codes to enable seamless localization and multilingual experiences. - Location search and ranking: Search for Google-supported locations by name and get results prioritized by reach, helping you target the most populous or relevant areas first. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `AUTOM_GOOGLE_COUNTRIES` | Google Countries | Search for Google-supported countries by name substring. Use this to get valid country codes for Google Search API parameters. Results are ordered by population reach (most populous countries first). | | `AUTOM_GOOGLE_IMAGES` | Google Images | Tool to fetch images from Google search results. Use when you need URLs, titles, domains, and metadata for images matching a query. | | `AUTOM_GOOGLE_LANGUAGES` | Google Languages | Tool to retrieve Google-supported languages. Use when you need a list of language codes for localization. | | `AUTOM_GOOGLE_LOCATIONS` | Google Locations | Tool to retrieve Google-supported locations. Use when searching for locations by name. Returns locations ordered by reach (most populous first). | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Autom MCP server is an implementation of the Model Context Protocol that connects your AI agent to Autom. It provides structured and secure access so your agent can perform Autom 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 Autom - 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 Autom - MCPServerStreamableHTTP connects to the Autom 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 Autom 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 Autom composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["autom"], ) 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 Autom endpoint - The agent uses GPT-5 to interpret user commands and perform Autom operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent autom_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[autom_mcp], instructions=( "You are a Autom assistant. Use Autom 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 - Autom 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 Autom.\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 Autom composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["autom"], ) 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 autom_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[autom_mcp], instructions=( "You are a Autom assistant. Use Autom 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 Autom.\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 Autom through Composio's Tool Router. With this setup, your agent can perform real Autom 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 + Autom 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 Autom MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/autom/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/autom/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/autom/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/autom/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/autom/framework/codex) - [OpenClaw](https://composio.dev/toolkits/autom/framework/openclaw) - [Hermes](https://composio.dev/toolkits/autom/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/autom/framework/cli) - [Google ADK](https://composio.dev/toolkits/autom/framework/google-adk) - [LangChain](https://composio.dev/toolkits/autom/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/autom/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/autom/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/autom/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/autom/framework/crew-ai) ## Related Toolkits - [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. It's the go-to tool for calculations, reporting, and flexible data management. - [21risk](https://composio.dev/toolkits/_21risk) - 21RISK is a web app built for easy checklist, audit, and compliance management. It streamlines risk processes so teams can focus on what matters. - [Abstract](https://composio.dev/toolkits/abstract) - Abstract provides a suite of APIs for automating data validation and enrichment tasks. It helps developers streamline workflows and ensure data quality with minimal effort. - [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time. - [Agentql](https://composio.dev/toolkits/agentql) - Agentql is a toolkit that connects AI agents to the web using a specialized query language. It enables structured web interaction and data extraction for smarter automations. - [Agenty](https://composio.dev/toolkits/agenty) - Agenty is a web scraping and automation platform for extracting data and automating browser tasks—no coding needed. It streamlines data collection, monitoring, and repetitive online actions. - [Ambee](https://composio.dev/toolkits/ambee) - Ambee is an environmental data platform providing real-time, hyperlocal APIs for air quality, weather, and pollen. Get precise environmental insights to power smarter decisions in your apps and workflows. - [Ambient weather](https://composio.dev/toolkits/ambient_weather) - Ambient Weather is a platform for personal weather stations with a robust API for accessing local, real-time, and historical weather data. Get detailed environmental insights directly from your own sensors for smarter apps and automations. - [Anonyflow](https://composio.dev/toolkits/anonyflow) - Anonyflow is a service for encryption-based data anonymization and secure data sharing. It helps organizations meet GDPR, CCPA, and HIPAA data privacy compliance requirements. - [Api ninjas](https://composio.dev/toolkits/api_ninjas) - Api ninjas offers 120+ public APIs spanning categories like weather, finance, sports, and more. Developers use it to supercharge apps with real-time data and actionable endpoints. - [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots. - [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. It lets you automate data extraction and workflow tasks at scale—no infrastructure headaches. - [Beaconchain](https://composio.dev/toolkits/beaconchain) - Beaconchain is a real-time analytics platform for Ethereum 2.0's Beacon Chain. It provides detailed insights into validators, blocks, and overall network performance. - [Big data cloud](https://composio.dev/toolkits/big_data_cloud) - BigDataCloud provides APIs for geolocation, reverse geocoding, and address validation. Instantly access reliable location intelligence to enhance your applications and workflows. - [Bigpicture io](https://composio.dev/toolkits/bigpicture_io) - BigPicture.io offers APIs for accessing detailed company and profile data. Instantly enrich your applications with up-to-date insights on 20M+ businesses. - [Bitquery](https://composio.dev/toolkits/bitquery) - Bitquery is a blockchain data platform offering indexed, real-time, and historical data from 40+ blockchains via GraphQL APIs. Get unified, reliable access to complex on-chain data for analytics, trading, and research. - [Brightdata](https://composio.dev/toolkits/brightdata) - Brightdata is a leading web data platform offering advanced scraping, SERP APIs, and anti-bot tools. It lets you collect public web data at scale, bypassing blocks and friction. - [Builtwith](https://composio.dev/toolkits/builtwith) - BuiltWith is a web technology profiler that uncovers the technologies powering any website. Gain actionable insights into analytics, hosting, and content management stacks for smarter research and lead generation. - [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation. - [Cabinpanda](https://composio.dev/toolkits/cabinpanda) - Cabinpanda is a data collection platform for building and managing online forms. It helps streamline how you gather, organize, and analyze responses. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Autom MCP? With a standalone Autom MCP server, the agents and LLMs can only access a fixed set of Autom tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Autom 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 Autom tools. ### Can I manage the permissions and scopes for Autom while using Tool Router? Yes, absolutely. You can configure which Autom 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 Autom data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)