Strava MCP Server

Strava MCP is a lightweight, protocol‑compliant server that exposes the full range of Strava’s activity and athlete data to AI assistants. By translating Strava’s REST API into the Model Context Protocol, it enables Claude and other MCP‑aware agents to query, analyze, and act on a user’s fitness records without needing custom integration code. This removes the friction of OAuth flows, pagination handling, and data normalization that developers normally have to implement when building fitness‑centric applications.

The server offers a set of resource endpoints that mirror Strava’s domain model: athletes, activities, routes, clubs, and segments. Each resource is available as a JSON schema that the AI can read to understand what fields are present and how they interrelate. Additionally, Strava MCP provides tool endpoints that let the assistant perform actions such as posting a new activity, updating an existing one, or adding comments to a segment. These tools are automatically surfaced in the AI’s context menu, allowing conversational agents to execute real‑world changes with a single command.

Key capabilities include:

• Contextual data fetching: Retrieve an athlete’s recent rides, distance totals, or segment leaderboard positions with simple queries.
• Actionability: Create or modify activities directly from the conversation, enabling workflows like “Log this workout” or “Add a comment to my latest run.”
• Event streaming: Subscribe to real‑time updates when new activities are posted, letting agents stay current with a user’s fitness progress.
• Rich metadata: Access GPS traces, elevation profiles, and performance metrics that can be fed into AI models for advanced analytics or coaching suggestions.

Typical use cases span personal fitness coaches, training planners, and health‑tracking apps. A virtual coach could ask a user about their weekly mileage, then automatically create a new activity entry after the workout. A data‑analysis assistant could pull elevation curves and suggest training zones, while a social platform could post activity highlights on behalf of the user. Because all interactions are mediated through MCP, developers can compose these features into larger workflows without writing bespoke API wrappers.

Strava MCP’s standout advantage is its seamless integration with existing AI pipelines. Developers can register the server once, and any MCP‑compatible assistant will automatically recognize Strava’s resources and tools. This eliminates repetitive authentication logic, guarantees consistent data schemas, and allows rapid prototyping of fitness‑focused conversational agents.