How to integrate Strava MCP with OpenAI Agents SDK

This guide walks you through connecting Strava to the OpenAI Agents SDK 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 OpenAI Agents SDK 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.

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Strava is a social fitness network and app for cyclists and runners. It's perfect for tracking workouts, sharing progress, and joining active communities.

33 Tools

Introduction

This guide walks you through connecting Strava to the OpenAI Agents SDK 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 OpenAI Agents SDK 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.

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TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Strava
  • Configure an AI agent that can use Strava as a tool
  • Run a live chat session where you can ask the agent to perform Strava operations

What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Strava project
  • Some knowledge of Python or Typescript
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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
3

Install dependencies

npm install @composio/openai-agents @openai/agents dotenv

Install the Composio SDK and the OpenAI Agents SDK.

4

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

5

Import dependencies

import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Strava.
6

Set up the Composio instance

dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
What's happening:
  • dotenv.config() loads your .env file so COMPOSIO_API_KEY and USER_ID are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.
7

Create a Tool Router session

// Create Tool Router session for Strava
const session = await composio.create(userId as string, {
  toolkits: ['strava'],
});
const mcpUrl = session.mcp.url;

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only strava.
  • The router checks the user's Strava connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Strava.
  • This approach keeps things lightweight and lets the agent request Strava tools only when needed during the conversation.
8

Configure the agent

// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access Strava. Help users perform Strava operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Strava and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a hostedMcpTool that connects to the MCP server URL we created earlier.
  • The headers object includes the Composio API key for secure authentication with the MCP server.
  • requireApproval: 'never' means the agent can execute Strava operations without asking for permission each time, making interactions smoother.
9

Start chat loop and handle conversation

// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

  if (!text) {
    rl.prompt();
    return;
  }

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
What's happening:
  • The program prints a session URL that you visit to authorize Strava.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using run().
  • The responses are printed to the console.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Strava and OpenAI Agents SDK:

import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['strava'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access Strava. Help users perform Strava operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

    if (!text) {
      rl.prompt();
      return;
    }

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\n');
    }

    rl.prompt();
  });

  rl.on('close', () => {
    console.log('\nSession ended.');
    process.exit(0);
  });
}

main().catch((err) => {
  console.error('Fatal error:', err);
  process.exit(1);
});

Conclusion

This was a starter code for integrating Strava MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Strava.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.
TOOLS

Supported Tools

Every Strava action and event your agent gets out of the box.

Create an Activity

Creates a manual activity for an athlete.

Explore segments

Explore segments within a geographic bounding box.

Export Route as GPX

Exports a Strava route as a GPX (GPS Exchange Format) file.

Export Route as TCX

Exports a Strava route as a TCX (Training Center XML) file.

Get Activity

Retrieves detailed information about a specific activity by its ID.

Get activity streams

Retrieves time-series stream data for a specific activity.

Get Activity Zones

Returns the heart rate and power zones of a given activity.

Get athlete stats

Returns the activity stats of an athlete, including ride, run, and swim totals for recent (last 4 weeks), year-to-date, and all-time periods.

Get authenticated athlete

Retrieves the profile of the currently authenticated Strava athlete.

Get Club

Retrieves detailed information about a specific Strava club by its ID.

Get equipment

Retrieves detailed information about a specific piece of gear/equipment.

Get route

Retrieve detailed information about a specific Strava route.

Get route streams

Get detailed stream data for a route.

Get segment

Retrieve detailed information about a specific Strava segment.

Get segment effort

Retrieves detailed information about a specific segment effort by its unique ID.

Get segment effort streams

Returns stream data for a segment effort completed by the authenticated athlete.

Get segment streams

Get detailed stream data for a segment.

Get Upload Status

Retrieves the status of an upload by its ID.

Get zones

Retrieves the authenticated athlete's heart rate and power zones.

List activity comments

Retrieves comments on a specific Strava activity, sorted oldest first.

List activity kudoers

Returns the athletes who kudoed an activity identified by an identifier.

List activity laps

Retrieves lap data for a specific Strava activity.

List athlete activities

Retrieves a paginated list of activities for the authenticated athlete.

List athlete clubs

Retrieves a paginated list of Strava clubs the authenticated athlete is a member of.

List athlete routes

Lists routes created by a specific athlete.

List club activities

Retrieve recent activities from members of a specific club.

List club administrators

Returns a list of the administrators of a given Strava club.

List club members

Returns a list of the athletes who are members of a given club.

List segment efforts

List the authenticated athlete's efforts on a given segment.

List starred segments

Returns a list of the authenticated athlete's starred segments with summary details including segment name, distance, elevation, grade, and location.

Star segment

Stars/Unstars the given segment for the authenticated athlete.

Update Athlete

Update the currently authenticated athlete's profile.

Upload Activity

Uploads a new activity file (FIT, TCX, or GPX) to create an activity on Strava.

FAQ

Frequently asked questions

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.

Yes, you can. OpenAI Agents SDK 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.

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.

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.

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