PluginBench
MCP Server
Active
MIT

HAPI Strava MCP Server MCP Server

ai.com.mcp/strava

Turn Strava APIs into AI-ready MCP tools instantly with HAPI—no rewrites, just OpenAPI specs.

What is the HAPI Strava MCP Server MCP server?

The HAPI Strava MCP Server automatically transforms Strava's OpenAPI specification into Model Context Protocol tools for AI agents. It exposes Strava's athlete, activity, segment, club, and route data as MCP-compatible tools without requiring custom code or service rewrites.

HAPI MCP lifts your existing OpenAPI specs directly into MCP tools, keeping your API logic unchanged while making it instantly available to AI agents like Claude and ChatGPT. For Strava, this means athletes, activities, segments, clubs, and routes become queryable tools—no parallel codebases, no integration sprawl, just your API as-is, AI-ready.

How to install HAPI Strava MCP Server

Copy-paste configuration for popular MCP clients.

transport: http
Config generated by PluginBench — verify against the source before use.
~/.cursor/mcp.json
{
  "mcpServers": {
    "strava": {
      "url": "https://strava.run.mcp.com.ai/mcp"
    }
  }
}

Tools & capabilities

Tools this server exposes to the agent.

  • Athletes — Query and retrieve athlete profiles and information from Strava
  • Activities — Access and manage Strava activities, including runs, rides, and other sports
  • Segments — Retrieve segment data and leaderboards from Strava
  • Clubs — Query club information and membership data
  • Routes — Access route data and planning information from Strava

Use cases

  • Query athlete performance metrics and activity history to analyze training patterns
  • Retrieve segment leaderboards and personal bests to track competitive progress
  • Access club information and member activities for team coordination
  • Plan routes using Strava's route data integrated into AI workflows
  • Analyze activity trends and statistics without leaving your AI agent interface

HAPI Strava MCP Server MCP server FAQ

What is the HAPI Strava MCP Server?

It's an MCP server that automatically exposes Strava's APIs (athletes, activities, segments, clubs, routes) as AI-ready tools. Built on HAPI MCP, it transforms OpenAPI specs into MCP tools without code rewrites.

Do I need to rewrite my Strava integration?

No. HAPI MCP lifts your existing OpenAPI specs directly into MCP tools. Your authentication, validation, and business rules remain unchanged.

Which AI clients can use this?

Any MCP-compatible client: Claude, ChatGPT, QBot, chatMCP, and custom orchestrators. It's vendor-neutral by design.

How do I install and connect it?

The server is available remotely at https://strava.run.mcp.com.ai/mcp. Add it to your MCP client configuration to start querying Strava data through AI agents.

Is authentication required?

Yes, you'll need valid Strava API credentials. HAPI MCP inherits your API's auth, permissions, and rate limits—no shadow logic or duplicate credentials.

How quickly can I get started?

You can have Strava tools available in your AI agent in minutes by connecting to the remote MCP endpoint. No local setup required.

README (reference)

Source of truth, from the repository.

HAPI MCP – Headless API for Model Context Protocol

Stop rewriting systems for AI. Instantly turn your APIs into MCP servers.

HAPI MCP lifts your OpenAPI catalog into MCP tools automatically, keeping design (OAS/Arazzo) and runtime (agents/LLMs) cleanly separated. Your existing APIs become AI-ready tools—no new business logic, no sidecar servers, no rework.

Key Features

  • No rewrites: Reuse 100% of your API logic. OpenAPI in, MCP tools out. No parallel codebase or shadow services.
  • Faster time-to-value: Turn specs into agent-ready tools in minutes. Update the spec, ship new tools instantly.
  • Reduced risk: Permissions, auth, rate limits, auditability are inherited from your APIs—governance without bolt-ons.
  • Scales with you: runMCP delivers serverless-like elasticity with long-running when needed. Cold-start fast, stay warm for throughput.
  • Deterministic orchestration: OrcA plans and executes multi-tool tasks predictably—no brittle prompt chaining.
  • Vendor-neutral: Works with any MCP client: ChatGPT, Claude, QBot, chatMCP. OAS + MCP + Arazzo stay portable.

How It Works

  1. Pick your API spec

    • OpenAPI, Swagger, REST—HAPI CLI works with any API specification format.
    • Supports OpenAPI 3.0+, REST APIs, OAuth 2.0 Dynamic Client Registration.
  2. Run a single command

    • One simple CLI command transforms your API into a usable MCP Server.
    • No complex setup, zero configuration, works anywhere, cross-platform.
  3. Use instantly

    • Your API is now ready as a tool, AI agent, or testing interface.
    • MCP server ready, AI agent compatible, testing interface, developer experience friendly.

Visual Pipeline

API Spec (swagger.json) → HAPI CLI → Usable Tool (AI-ready) ← MCP Clients
[ OpenAPI / Swagger ]       [ HAPI CLI ]        [ MCP Server ]
       (Your API)         →   (Transform)   →   (Usable Tool)
                                                 ↑          ↑
                                                 |          |
                                          [ ChatGPT ]  [ runMCP ]
                                          [ Claude  ]  [ OrcA   ]
                                          [ QBot    ]  [ chatMCP]
                                          [ Agents  ]

Who Wins With HAPI

  • Executives: Ship AI initiatives without ballooning cost. Keep teams focused on outcomes, not rewrites and integration sprawl.
  • Architects & PMs: Design with OpenAPI/Arazzo, run with MCP. Clear contracts, policy inheritance, and versioned workflows keep risk low.
  • Engineers & Ops: Deploy once. HAPI Server + runMCP scale tools; QBot/chatMCP give fast feedback; OrcA keeps executions deterministic.

Your Stack, Already Wired

  • HAPI Server: Turns OpenAPI into MCP tools automatically—contracts stay in sync with your source of truth.
  • runMCP: Autoscaling execution and testing for MCP tools; cold-start fast, stay warm when workflows run long.
  • QBot: CLI TUI for power users to interact with MCP tools directly from terminal or scripts.
  • chatMCP: Conversational client that speaks MCP natively for support, ops, and internal assistants.
  • OrcA: Deterministic planning and orchestration for multi-tool tasks; no brittle prompt spaghetti.
  • Agents: Build agentic systems from standard APIs—no custom glue. Connect MCP clients across platforms.

Demos

Documentation

FAQ

  • Do we need to rewrite our services?
    No. HAPI MCP lifts your existing OpenAPI specs directly into MCP tools. Your auth, validation, and business rules remain unchanged.

  • Is this just another MCP server?
    It’s the Headless API model: your API becomes the runtime. HAPI Server reflects it as MCP; runMCP scales it; OrcA orchestrates it. No duplicate logic.

  • Which clients can consume the tools?
    Any MCP client: ChatGPT, Claude, QBot, chatMCP, bespoke orchestrators—vendor-neutral by design.

  • How do we keep control and compliance?
    Your API remains the single source of truth. Policies, RBAC, rate limits, and audit logs flow through automatically; no shadow logic.

  • What about security and privacy?
    Scoped credentials, per-tool permissions, and auditable calls are inherited from your API layer. HAPI adds guardrails and observability for regulated environments.

  • How fast can we get started?
    You can transform your first API into an MCP tool in less than five minutes. The HAPI CLI makes it quick and painless.

Get Started

  1. Install HAPI CLI from latest release: https://github.com/la-rebelion/hapimcp/releases

  2. Transform your OpenAPI spec into an MCP server with a single command:

    hapi serve path/to/your/swagger.json --headless
    
  3. Start using your MCP tools with any compatible client!

  4. Explore the documentation for advanced usage and best practices.

Contributing

Contributions are welcome! Open a discussion or submit a pull request on GitHub: https://github.com/la-rebelion/hapimcp

License

HAPI MCP is licensed under the MIT License. See LICENSE for details.

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