# How to integrate Piloterr MCP with Pydantic AI ```json { "title": "How to integrate Piloterr MCP with Pydantic AI", "toolkit": "Piloterr", "toolkit_slug": "piloterr", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/piloterr/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/piloterr/framework/pydantic-ai.md", "updated_at": "2026-05-12T10:21:58.411Z" } ``` ## Introduction This guide walks you through connecting Piloterr to Pydantic AI using the Composio tool router. By the end, you'll have a working Piloterr agent that can find trending laptops on bestbuy today, get full details for auchan product id 12345, search for organic snacks on auchan through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Piloterr account through Composio's Piloterr MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Piloterr with - [OpenAI Agents SDK](https://composio.dev/toolkits/piloterr/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/piloterr/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/piloterr/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/piloterr/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/piloterr/framework/codex) - [OpenClaw](https://composio.dev/toolkits/piloterr/framework/openclaw) - [Hermes](https://composio.dev/toolkits/piloterr/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/piloterr/framework/cli) - [Google ADK](https://composio.dev/toolkits/piloterr/framework/google-adk) - [LangChain](https://composio.dev/toolkits/piloterr/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/piloterr/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/piloterr/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/piloterr/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/piloterr/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 Piloterr - 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 Piloterr 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 Piloterr MCP server, and what's possible with it? The Piloterr MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Piloterr account. It provides structured and secure access to a suite of powerful web data extraction APIs, so your agent can perform actions like searching products, retrieving detailed product info, and monitoring account usage on your behalf. - Product search on retail platforms: Direct your agent to search for products on sites like Auchan or Bestbuy by keyword, category, or filters, and receive curated product listings. - Retrieve detailed product information: Ask your agent to fetch comprehensive product details—including company info—using specific product IDs from supported platforms. - Monitor account usage and credits: Let your agent check your Piloterr account usage and remaining credits, so you always know how much data access you have left. - Automated product data workflows: Enable your agent to seamlessly combine product search and retrieval, powering advanced e-commerce, analytics, or market research tasks. - Multi-platform product integration: Effortlessly access and aggregate product data from multiple online stores to inform business decisions or drive automation. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `PILOTERR_AUCHAN_PRODUCT` | Auchan Product | Tool to retrieve detailed Auchan product information. Use when you have an Auchan product URL. | | `PILOTERR_AUCHAN_SEARCH` | Auchan Product Search | Tool to search for products on Auchan by query or search URL. Use when you need product listings and details from Auchan. | | `PILOTERR_GET_PRODUCT_INFO` | Piloterr Get Product Info | Tool to retrieve detailed product information from G2. Use when you need full product details including ratings, reviews, pricing, and company info. Accepts a product name or G2 URL as query. | | `PILOTERR_LIST_CHEWY_PRODUCTS` | List Chewy Products | Tool to find Chewy product categories by search query. Use when you need to retrieve Chewy product URLs and details based on product ID or title. | | `PILOTERR_LIST_ELECLERC_STORES` | List E.Leclerc Stores | Tool to find E.Leclerc store locations by search query. Use when you need to locate E.Leclerc stores in a specific area or city. | | `PILOTERR_LIST_GOOGLE_COUNTRIES` | List Google Countries | Tool to list available Google search countries. Use when you need to find country codes for Google search localization. | | `PILOTERR_LIST_GOOGLE_LANGUAGES` | List Google Languages | Tool to list available Google search languages filtered by query. Use when you need to find specific language codes for Google searches. | | `PILOTERR_LIST_GOOGLE_LOCATIONS` | List Google Locations | Tool to list available Google search locations via Piloterr API. Use when you need to find location identifiers for geographically-targeted searches. | | `PILOTERR_LIST_LEROY_MERLIN_PRODUCTS` | List Leroy Merlin Products | Tool to list Leroy Merlin product categories. Use when you need to search for Leroy Merlin products by name or identifier. | | `PILOTERR_LIST_LINKED_IN_INDUSTRIES` | List LinkedIn Industries | Tool to list LinkedIn industry codes from Piloterr API. Use when you need to find LinkedIn industry identifiers for targeting or classification. | | `PILOTERR_SEARCH` | Piloterr Google Search | Tool to perform Google web search via Piloterr API. Use when you need to search the web for information using Google. | | `PILOTERR_USAGE_GET` | Get Usage | Tool to get usage information and remaining credits for your Piloterr account. Use when you need to check account usage and credit details. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Piloterr MCP server is an implementation of the Model Context Protocol that connects your AI agent to Piloterr. It provides structured and secure access so your agent can perform Piloterr 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 Piloterr - 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 Piloterr - MCPServerStreamableHTTP connects to the Piloterr 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 Piloterr 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 Piloterr composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["piloterr"], ) 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 Piloterr endpoint - The agent uses GPT-5 to interpret user commands and perform Piloterr operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent piloterr_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[piloterr_mcp], instructions=( "You are a Piloterr assistant. Use Piloterr 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 - Piloterr 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 Piloterr.\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 Piloterr composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["piloterr"], ) 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 piloterr_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[piloterr_mcp], instructions=( "You are a Piloterr assistant. Use Piloterr 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 Piloterr.\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 Piloterr through Composio's Tool Router. With this setup, your agent can perform real Piloterr 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 + Piloterr 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 Piloterr MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/piloterr/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/piloterr/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/piloterr/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/piloterr/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/piloterr/framework/codex) - [OpenClaw](https://composio.dev/toolkits/piloterr/framework/openclaw) - [Hermes](https://composio.dev/toolkits/piloterr/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/piloterr/framework/cli) - [Google ADK](https://composio.dev/toolkits/piloterr/framework/google-adk) - [LangChain](https://composio.dev/toolkits/piloterr/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/piloterr/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/piloterr/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/piloterr/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/piloterr/framework/crew-ai) ## Related Toolkits - [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. 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It helps streamline how you gather, organize, and analyze responses. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Piloterr MCP? With a standalone Piloterr MCP server, the agents and LLMs can only access a fixed set of Piloterr tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Piloterr 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 Piloterr tools. ### Can I manage the permissions and scopes for Piloterr while using Tool Router? Yes, absolutely. You can configure which Piloterr 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 Piloterr data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)