Strava MCP Server

Overview

The Ctvidic Strava MCP Server bridges the gap between AI assistants and the rich data ecosystem of Strava. By exposing a Model Context Protocol interface, it lets language models such as Claude query, analyze, and visualize athletic activity data without leaving the conversational context. This solves a common pain point for developers building fitness‑centric applications: integrating authenticated, real‑time Strava data into natural language workflows while preserving privacy and security.

The server authenticates with the Strava API using OAuth 2.0 credentials supplied in a configuration file, then offers a set of high‑level tools that translate user intent into Strava API calls. When an assistant receives a prompt like “Show me my longest ride this month,” the MCP server interprets the request, fetches the relevant activity records, and returns a concise summary. It can also provide richer outputs such as route maps or heart‑rate profiles, allowing the model to embed visualizations directly into chat messages. This tight coupling eliminates the need for developers to write custom adapters or manage token refresh logic.

Key capabilities include:

• Activity tracking and analysis – list recent rides, runs, or swims; compute pace, elevation gain, and training load.
• Athlete statistics – aggregate year‑to‑date totals, personal records, and equipment usage.
• Route visualization – deliver map tiles with elevation overlays or segment heatmaps, enabling route planning and comparison.
• Social interactions – expose kudos, comments, club activities, and friend challenges for a more connected experience.
• Achievement tracking – surface segment efforts, personal records, and goal progress in natural language.

Real‑world use cases span from fitness coaching platforms that want to surface personalized insights during a chat, to health‑tech dashboards where an assistant can answer “How many miles did I run last week?” and instantly display the data. Developers can embed the MCP server into their own desktop or web stacks, configuring it as a local process that Claude Desktop can launch via the section of its settings. Alternatively, the same codebase can be run as a lightweight HTTP API on , offering REST endpoints that other services can consume.

What sets this server apart is its dual‑mode operation: a seamless MCP integration for conversational agents and a standalone HTTP API for traditional applications, all while handling authentication, rate limiting, and data caching transparently. By centralizing Strava interactions behind a single protocol layer, it empowers developers to focus on building engaging user experiences rather than plumbing data access.