Strava MCP

A Model Context Protocol (MCP) server that supplements the official Strava MCP connector. It adds write access, segments, routes, photos, derived analysis, and interactive visualizations that the official connector does not provide.

Features

• Write and update activities (title, description, sport type, gear, flags)
• Create manual activities for sessions with no device recording (strength, yoga, treadmill)
• Explore, view, star, and manage segments
• Fetch per-activity photos, zone breakdowns, and running summaries
• List and view details of saved routes
• Export routes (GPX/TCX) and activity tracks (GPX built from streams)
• Derived analysis Strava does not expose: interval detection, climb/descent breakdown, aerobic decoupling, training load, fitness/fatigue/form (CTL/ATL/TSB), and a solved taper to a target race-day form
• AI-friendly JSON responses via MCP
• Nine interactive visualizations rendered in MCP-compatible hosts — activity chart, cadence trends, route map, activity segments, training load, compare activities, activity zones, segment progress, and fitness trend
• Guided prompts for weekly reviews, annotating a run, and segment hunting (docs/tools.md)
• Automatic token refresh
• Streamable HTTP transport for remote deployment

Browse the UI components in the live Storybook.

The full tool catalog, prompts, permission behaviour, and example requests live in docs/tools.md.

Quick Start (Docker)

1. Create a Strava API Application

1. Go to strava.com/settings/api
2. Create a new application:
   • Enter your application details (name, website, description)
   • Set "Authorization Callback Domain" to your public URL hostname (e.g., strava-mcp.example.com)
   • Note your Client ID and Client Secret

2. Configure Environment

cp .env.example .env

Edit .env with your values:

STRAVA_CLIENT_ID=your_client_id
STRAVA_CLIENT_SECRET=your_client_secret
PUBLIC_URL=https://your-public-url.example.com

All variables are listed in docs/operations.md. Prefer the prebuilt image? Pull ghcr.io/ljcl/strava-mcp:latest (also on the MCP registry as io.github.ljcl/strava-mcp) and point your compose image: at it instead of building; you still supply the Strava credentials yourself. Published images carry SBOM/provenance attestations you can verify — see operations.md.

Note on the ./data bind mount: tokens persist there, and the distroless image runs as non-root UID 65534, so the directory must be writable by that UID or token persistence fails on first run:

mkdir -p data
sudo chown -R 65534:65534 data

Alternatively use a named volume in docker-compose.yml (e.g. strava-data:/app/data), which Docker initializes with correct ownership. More detail in operations.md.

3. Start the Server

docker compose up -d

GET /health reports liveness without spending a Strava API request; with MCP_AUTH_TOKEN it also reports auth and rate-limit state. Response shapes and monitoring guidance: operations.md.

4. Authorize with Strava

Visit https://your-public-url/auth/start in your browser. After authorizing, tokens are saved automatically and refreshed from then on. Check status anytime at /auth/status.

If you set MCP_AUTH_TOKEN, append it to both URLs as ?token=<MCP_AUTH_TOKEN>.

5. Connect to Claude Desktop

Add to your Claude configuration (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "strava": {
      "type": "url",
      "url": "https://your-public-url/mcp",
      "headers": { "Authorization": "Bearer your-mcp-auth-token" }
    }
  }
}

The headers entry is only needed when MCP_AUTH_TOKEN is set (recommended for tunnel-exposed servers — see Securing the endpoint).

Restart Claude Desktop to load the new configuration.

Connecting to AI Tools

Most AI tools (Claude Desktop, Claude Code, etc.) need an HTTPS URL to reach your MCP server. Since the server runs on your local network, you'll need a tunnel to expose it.

Tailscale Funnel (Recommended)

Tailscale Funnel exposes a local port to the internet over HTTPS with no configuration:

tailscale funnel --bg 3000
# → https://your-machine.tail1234.ts.net

Set PUBLIC_URL in your .env to the resulting URL.

Cloudflare Tunnel

cloudflared tunnel --url http://localhost:3000

Securing the endpoint

A tunnel makes /mcp reachable by anyone who discovers the URL — including the update-activity write tool. Set MCP_AUTH_TOKEN to a long random secret (openssl rand -hex 32) and every /mcp request requires Authorization: Bearer <token>; each client snippet below shows where the header goes. The secret also gates /auth/start and /auth/status. Full details (including how OAuth callbacks stay safe): operations.md.

Set it in .env alongside your Strava credentials — docker-compose.yml forwards it automatically.

AI Tool (Claude Desktop, Claude Code, etc.)
    │  HTTPS
HTTPS Tunnel (Tailscale / Cloudflare)
    │  HTTP (localhost:3000)
Strava MCP Server (Docker / Bun)
    │  HTTPS
Strava API

Client configuration

The server works with any MCP client that supports the Streamable HTTP transport. In every snippet below, replace https://your-public-url with your tunnel URL (or http://localhost:3000 for local development), and include the Authorization header only if you set MCP_AUTH_TOKEN.

Claude Code

claude mcp add --transport http strava https://your-public-url/mcp \
  --header "Authorization: Bearer your-mcp-auth-token"

Cursor

Add to .cursor/mcp.json in your project (or ~/.cursor/mcp.json for all projects):

{
  "mcpServers": {
    "strava": {
      "url": "https://your-public-url/mcp",
      "headers": { "Authorization": "Bearer your-mcp-auth-token" }
    }
  }
}

VS Code

Add to .vscode/mcp.json in your workspace (or run MCP: Add Server from the command palette):

{
  "servers": {
    "strava": {
      "type": "http",
      "url": "https://your-public-url/mcp",
      "headers": { "Authorization": "Bearer your-mcp-auth-token" }
    }
  }
}

Other clients (generic Streamable HTTP)

Any client that speaks Streamable HTTP can connect to the /mcp endpoint directly. One URL serves both protocol eras: 2026-07-28 clients send stateless requests carrying the io.modelcontextprotocol/* envelope keys (server/discover advertises capabilities); 2025-era clients use the ordinary initialize handshake. POST JSON-RPC messages with an Accept: application/json, text/event-stream header. Protocol details: docs/architecture.md.

Using alongside the official Strava MCP

Strava's official MCP connector handles activity discovery and basic reads. This server supplements it with everything the official connector does not offer: writing to activities, segments, routes and GPX/TCX export, photos, derived analysis, and interactive visualizations.

Install both

• Official: claude mcp add --transport http strava-mcp https://mcp.strava.com/mcp (or via claude.ai Connectors / Claude Desktop).
• This server: see the install steps above.

Who does what

Caveats

• The official connector requires a Strava subscription and currently runs only in Anthropic clients.
• With the duplicate reads removed, this server now effectively assumes the official connector is installed for activity discovery. The aggregate analysis tools (get-best-efforts, get-training-load) fetch their own activity lists, but per-activity tools (get-running-summary, compare-activities, get-activity-zones, etc.) need an activity id from the official list_activities.
• The two use separate rate-limit quotas, so running both spreads API load.

Recommended workflow

Use the official connector to discover and read activities, then use this server to write, explore segments, manage and export routes, and visualize. The model can pass activity ids from official list_activities directly into this server's tools.

Example requests

Ask your AI assistant questions like these (use the official Strava MCP to discover activity IDs, then pass them to these tools):