# How to integrate Strava MCP with Pydantic AI ```json { "title": "How to integrate Strava MCP with Pydantic AI", "toolkit": "Strava", "toolkit_slug": "strava", "framework": "Pydantic AI", "framework_slug": "pydantic-ai", "url": "https://composio.dev/toolkits/strava/framework/pydantic-ai", "markdown_url": "https://composio.dev/toolkits/strava/framework/pydantic-ai.md", "updated_at": "2026-05-06T08:30:02.740Z" } ``` ## Introduction This guide walks you through connecting Strava to Pydantic AI using the Composio tool router. By the end, you'll have a working Strava agent that can get your latest cycling activity stats, list all runs i logged this week, show your longest ride from last month through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Strava account through Composio's Strava MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Strava with - [ChatGPT](https://composio.dev/toolkits/strava/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/strava/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/strava/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/strava/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/strava/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/strava/framework/codex) - [Cursor](https://composio.dev/toolkits/strava/framework/cursor) - [VS Code](https://composio.dev/toolkits/strava/framework/vscode) - [OpenCode](https://composio.dev/toolkits/strava/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/strava/framework/openclaw) - [Hermes](https://composio.dev/toolkits/strava/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/strava/framework/cli) - [Google ADK](https://composio.dev/toolkits/strava/framework/google-adk) - [LangChain](https://composio.dev/toolkits/strava/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/strava/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/strava/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/strava/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/strava/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 Strava - 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 Strava 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 Strava MCP server, and what's possible with it? The Strava MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Strava account. It provides structured and secure access to your fitness data, so your agent can perform actions like fetching activities, analyzing stats, logging workouts, managing routes, and exploring your social fitness feed on your behalf. - Workout tracking and retrieval: Let your agent pull detailed records of your recent runs, rides, and other logged activities, complete with stats, maps, and performance data. - Fitness analytics and progress insights: Have your agent analyze your weekly or monthly trends, highlight PRs, and summarize progress toward your training goals. - Route exploration and management: Ask your agent to list, suggest, or organize your favorite routes and segments for upcoming workouts or challenges. - Social engagement automation: Enable your agent to fetch kudos, summarize comments, or surface activity highlights from friends and clubs in your Strava network. - Activity creation and editing: Allow your agent to log new activities, edit workout details, or update activity metadata for accurate record keeping. ## Supported Tools None listed. ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Strava MCP server is an implementation of the Model Context Protocol that connects your AI agent to Strava. It provides structured and secure access so your agent can perform Strava 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 Strava - 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 Strava - MCPServerStreamableHTTP connects to the Strava 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 Strava 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 Strava composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["strava"], ) 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 Strava endpoint - The agent uses GPT-5 to interpret user commands and perform Strava operations - The instructions field defines the agent's role and behavior ```python # Attach the MCP server to a Pydantic AI Agent strava_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[strava_mcp], instructions=( "You are a Strava assistant. Use Strava 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 - Strava 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 Strava.\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 Strava composio = Composio(api_key=api_key) session = composio.create( user_id=user_id, toolkits=["strava"], ) 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 strava_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY}) agent = Agent( "openai:gpt-5", toolsets=[strava_mcp], instructions=( "You are a Strava assistant. Use Strava 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 Strava.\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 Strava through Composio's Tool Router. With this setup, your agent can perform real Strava 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 + Strava 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 Strava MCP Agent with another framework - [ChatGPT](https://composio.dev/toolkits/strava/framework/chatgpt) - [OpenAI Agents SDK](https://composio.dev/toolkits/strava/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/strava/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/strava/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/strava/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/strava/framework/codex) - [Cursor](https://composio.dev/toolkits/strava/framework/cursor) - [VS Code](https://composio.dev/toolkits/strava/framework/vscode) - [OpenCode](https://composio.dev/toolkits/strava/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/strava/framework/openclaw) - [Hermes](https://composio.dev/toolkits/strava/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/strava/framework/cli) - [Google ADK](https://composio.dev/toolkits/strava/framework/google-adk) - [LangChain](https://composio.dev/toolkits/strava/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/strava/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/strava/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/strava/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/strava/framework/crew-ai) ## Related Toolkits - [Twitter](https://composio.dev/toolkits/twitter) - Twitter is a social media platform for sharing real-time updates, conversations, and news. Stay connected, informed, and engaged with communities worldwide. - [Instagram](https://composio.dev/toolkits/instagram) - Instagram is a social platform for sharing photos, videos, and stories with your audience. It helps brands and creators engage, grow, and analyze their online presence. - [Ayrshare](https://composio.dev/toolkits/ayrshare) - Ayrshare is a Social Media API for managing, automating, and analyzing posts across multiple platforms. It helps you streamline social media workflows and centralize analytics. - [Dotsimple](https://composio.dev/toolkits/dotsimple) - Dotsimple is a social media management platform for planning, creating, and publishing content. It helps teams boost their reach with AI-powered content generation and actionable analytics. - [Tiktok](https://composio.dev/toolkits/tiktok) - Tiktok is a short-form video platform for creating, sharing, and discovering viral content. It helps creators and brands reach massive audiences with creative tools and global social features. - [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable. - [Google Calendar](https://composio.dev/toolkits/googlecalendar) - Google Calendar is a time management service for scheduling meetings, events, and reminders. It streamlines personal and team organization with integrated notifications and sharing options. - [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices. - [Outlook](https://composio.dev/toolkits/outlook) - Outlook is Microsoft's email and calendaring platform for unified communications and scheduling. It helps users stay organized with powerful email, contacts, and calendar management. - [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly. - [Supabase](https://composio.dev/toolkits/supabase) - Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. It lets developers build modern apps without managing infrastructure. - [Composio](https://composio.dev/toolkits/composio) - Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed. - [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place. - [Slack](https://composio.dev/toolkits/slack) - Slack is a channel-based messaging platform for teams and organizations. It helps people collaborate in real time, share files, and connect all their tools in one place. - [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations. - [Google Docs](https://composio.dev/toolkits/googledocs) - Google Docs is a cloud-based word processor that enables document creation and real-time collaboration. Its seamless sharing and version history make team editing and content management a breeze. - [Google Super](https://composio.dev/toolkits/googlesuper) - Google Super is an all-in-one suite combining Gmail, Drive, Calendar, Sheets, Analytics, and more. It gives you a unified platform to manage your digital life, boosting productivity and organization. - [Hubspot](https://composio.dev/toolkits/hubspot) - HubSpot is an all-in-one marketing, sales, and customer service platform. It lets teams nurture leads, automate outreach, and track every customer interaction in one place. - [Codeinterpreter](https://composio.dev/toolkits/codeinterpreter) - Codeinterpreter is a Python-based coding environment with built-in data analysis and visualization. It lets you instantly run scripts, plot results, and prototype solutions inside supported platforms. - [Gong](https://composio.dev/toolkits/gong) - Gong is a platform for video meetings, call recording, and team collaboration. It helps teams capture conversations, analyze calls, and turn insights into action. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Strava MCP? With a standalone Strava MCP server, the agents and LLMs can only access a fixed set of Strava tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Strava 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 Strava tools. ### Can I manage the permissions and scopes for Strava while using Tool Router? Yes, absolutely. You can configure which Strava 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 Strava data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)