Can I see who liked my activities?

Yes! Use the get_activity_kudos tool with any activity ID. It returns the full list of athletes who gave kudos to that activity, including their names, cities, and profile pictures. This helps you understand who's following and supporting your training.

How can I discover popular segments in a new city?

Use the explore_segments tool with a bounding box of the area you're interested in. The bounds format is "southwest_lng,southwest_lat,northeast_lng,northeast_lat". For example, "-74.00,40.70,-73.95,40.75" covers Manhattan. You can filter by activity_type ("riding" or "running") and difficulty category (0-5, where 0 is hardest).

Can I see what my club members have been doing?

Yes! Use list_club_activities with the club ID. It returns the 30 most recent activities from club members with athlete names, activity types, distances, and dates. Paginate through results to see more. This is great for staying connected with your training group's activities.

Strava Social MCP Server for Mastra AI 10 tools — connect in under 2 minutes

Name: Strava Social
Availability: InStock
Author: Vinkius

docs.mastra.ai/docs/agents/mcp-tools

Built by Vinkius GDPR 10 Tools SDK

Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Strava Social through the Vinkius and Mastra agents discover all tools automatically — type-safe, streaming-ready, and deployable anywhere Node.js runs.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

typescript

import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";

async function main() {
  // Your Vinkius token — get it at cloud.vinkius.com
  const mcpClient = await createMCPClient({
    servers: {
      "strava-social": {
        url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
      },
    },
  });

  const tools = await mcpClient.getTools();
  const agent = new Agent({
    name: "Strava Social Agent",
    instructions:
      "You help users interact with Strava Social " +
      "using 10 tools.",
    model: openai("gpt-4o"),
    tools,
  });

  const result = await agent.generate(
    "What can I do with Strava Social?"
  );
  console.log(result.text);
}

main();

Fully ManagedVinkius Servers

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IAMAccess control

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DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Strava Social MCP Server

Connect Strava Social to any AI agent and explore the social side of Strava — activity feeds, kudos, comments, club memberships, and segment discovery.

Mastra's agent abstraction provides a clean separation between LLM logic and Strava Social tool infrastructure. Connect 10 tools through the Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution — deployable to any Node.js host in one command.

What you can do

Activity Feed — Browse your recent activities with full details, kudos counts, and comment counts
Activity Comments — Read all comments on any activity with author names and text
Activity Kudos — See who liked/supports your activities with full athlete profiles
Athlete Profile — Get your Strava profile details including location, follower counts, and equipment
Club Membership — List all clubs you belong to with member counts and sport types
Club Details — Explore any club's description, location, and community focus
Club Members — Browse club membership to find training partners and local athletes
Club Activities — See what club members have been doing recently
Starred Segments — Review all your favorited segments with PR times and characteristics
Segment Discovery — Explore segments in any geographic area by bounding box, filterable by type and difficulty

The Strava Social MCP Server exposes 10 tools through the Vinkius. Connect it to Mastra AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Strava Social to Mastra AI via MCP

Follow these steps to integrate the Strava Social MCP Server with Mastra AI.

Install dependencies

Run npm install @mastra/core @mastra/mcp @ai-sdk/openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.ts and run with npx tsx agent.ts

Explore tools

Mastra discovers 10 tools from Strava Social via MCP

Why Use Mastra AI with the Strava Social MCP Server

Mastra AI provides unique advantages when paired with Strava Social through the Model Context Protocol.

Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure — add Strava Social without touching business code

Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation

TypeScript-native: full type inference for every Strava Social tool response with IDE autocomplete and compile-time checks

One-command deployment to any Node.js host — Vercel, Railway, Fly.io, or your own infrastructure

Strava Social + Mastra AI Use Cases

Practical scenarios where Mastra AI combined with the Strava Social MCP Server delivers measurable value.

Automated workflows: build multi-step agents that query Strava Social, process results, and trigger downstream actions in a typed pipeline

SaaS integrations: embed Strava Social as a first-class tool in your product's AI features with Mastra's clean agent API

Background jobs: schedule Mastra agents to query Strava Social on a cron and store results in your database automatically

Multi-agent systems: create specialist agents that collaborate using Strava Social tools alongside other MCP servers

Strava Social MCP Tools for Mastra AI (10)

These 10 tools become available when you connect Strava Social to Mastra AI via MCP:

explore_segments

g., "-74.00,40.70,-73.95,40.75" for Manhattan). Optional filters: activity_type ("running" or "riding"), min_cat/max_cat (category 0-5, where 0 is hardest/steepest). Returns segments with name, distance, elevation, grade, and climb category. Use this to discover new training routes, find popular segments in an area, or plan rides/runs in a new city. Explore and discover Strava segments in a geographic area

get_activity_comments

Each comment includes athlete name, text, and creation date. The activityId is the numeric ID from Strava activity URLs. Use this to see community engagement on a workout, read feedback, or track conversation around a specific activity. Get all comments on a specific Strava activity

get_activity_kudos

Each entry includes athlete name, profile picture, and city. The activityId is the numeric ID from Strava. Use this to see who supported an activity, understand social engagement, or track training partners' interactions. Get the list of athletes who gave kudos (likes) to a specific activity

get_athlete

Use this to understand the athlete's identity, location, and equipment setup. Get the authenticated athlete's profile information

get_club

The clubId is found in Strava club URLs. Use this to explore club details before joining or to understand a club's focus and community. Get detailed information about a specific Strava club

list_activities

Activities are sorted by most recent first. Optional filters: "before" (epoch timestamp, defaults to now), "after" (epoch timestamp for date range), "page" and "per_page" (pagination, max 200 per page, max 2000 total). Each activity includes: name, type, distance, moving_time, elevation, kudos_count, comment_count, start_date, and basic stats. Use this to get the activity feed, analyze recent workouts, or review training history. Epoch timestamps can be generated from dates. List the authenticated athlete's activities with optional date filtering and pagination

list_athlete_clubs

Each club includes name, member count, city, country, sport type (cycling/running/triathlon), and privacy status. Use this to discover club memberships, find training groups, or understand community affiliations. List all clubs the authenticated athlete belongs to

list_club_activities

Each entry includes athlete name, activity name, type, distance, and date. Paginated (30 per page). The clubId is from Strava club URLs. Use this to stay updated on club training activity, discover what members are doing, or find group workout opportunities. Get recent activities from members of a Strava club

list_club_members

Paginated (30 per page). The clubId is from Strava club URLs. Use this to discover training partners in a club, find athletes in your area, or explore club community composition. List members of a specific Strava club

list_starred_segments

Each segment includes: name, distance, elevation gain, average grade, activity type, city, country, and the athlete's PR time if any. Use this to review favorite segments, plan training routes, or track progress on key segments over time. List all segments starred (favorited) by the authenticated athlete