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Vinkius
LlamaIndexFramework
LlamaIndex
Why use Strava Social MCP Server with LlamaIndex?

Bring Activity Tracking
to LlamaIndex

Create your Vinkius account to connect Strava Social to LlamaIndex and start using all 10 AI tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code. No hosting, no server setup — just connect and start using.

MCP Inspector GDPR Free for Subscribers
Explore SegmentsGet Activity CommentsGet Activity KudosGet AthleteGet ClubList ActivitiesList Athlete ClubsList Club ActivitiesList Club MembersList Starred Segments
ChatGPT Claude Perplexity

Compatible with every major AI agent and IDE

ClaudeClaude
ChatGPTChatGPT
CursorCursor
GeminiGemini
WindsurfWindsurf
VS CodeVS Code
JetBrainsJetBrains
VercelVercel
+ other MCP clients
Strava Social

What is the 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.

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

How it works

  1. Subscribe to this server
  2. Enter your Strava Access Token (OAuth2)
  3. Start exploring your Strava social network from Claude, Cursor, or any MCP-compatible client

Who is this for?

  • Social Athletes — stay engaged with training partners, track kudos and community interaction
  • Club Organizers — monitor club activity levels, member engagement, and discover new training routes
  • Training Groups — explore what teammates are doing, find popular segments in your area
  • New City Explorers — discover popular cycling/running segments when traveling to new cities

Built-in capabilities (10)

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

Why LlamaIndex?

LlamaIndex agents combine Strava Social tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

  • Data-first architecture: LlamaIndex agents combine Strava Social tool responses with indexed documents for comprehensive, grounded answers

  • Query pipeline framework lets you chain Strava Social tool calls with transformations, filters, and re-rankers in a typed pipeline

  • Multi-source reasoning: agents can query Strava Social, a vector store, and a SQL database in a single turn and synthesize results

  • Observability integrations show exactly what Strava Social tools were called, what data was returned, and how it influenced the final answer

L
See it in action

Strava Social in LlamaIndex

AI AgentVinkius
High Security·Kill Switch·Plug and Play
Enterprise Security

Why run Strava Social with Vinkius?

The Strava Social connection runs on our fully managed, secure cloud infrastructure. We handle the hosting, maintenance, and security so you don't have to deal with servers or code. All 10 tools are ready to work instantly without any complex setup.

You stay in complete control of your data. Your AI only accesses the information you approve, keeping your sensitive passwords and private details completely safe. Plus, with automatic optimizations, your AI works faster and more efficiently.

Strava Social
Fully ManagedNo server setup
Plug & PlayNo coding needed
SecurePrivacy protected
PrivateYour data is safe
Cost ControlBudget limits
Control1-click disconnect
Auto-UpdatesMaintenance free
High SpeedOptimized for AI
Reliable99.9% uptime
Your credentials and connection tokens are fully encrypted

* Every connection is hosted and maintained by Vinkius. We handle the security, updates, and infrastructure so you don't have to write code or manage servers. See our infrastructure

01 / Catalog

Over 4,000 integrations ready for AI agents

Explore a vast library of pre-built integrations, optimized and ready to deploy.

02 / Credentials

Connect securely in under 30 seconds

Generate tokens to authenticate and link external services in a single step.

03 / Guardian

Complete visibility into every agent action

Audit live requests, latency, success rates, and active security compliance policies.

04 / FinOps

Optimize spending and track token ROI

Analyze real-time token consumption and cost metrics detailed by connection.

Over 4,000 integrations ready for AI agents
Connect securely in under 30 seconds
Complete visibility into every agent action
Optimize spending and track token ROI

Explore our live AI Agents Analytics dashboard to see it all working

This dashboard is included when you connect Strava Social using Vinkius. You will never be left in the dark about what your AI agents are doing with your tools.

Why Vinkius

Strava Social and 4,000+ other AI tools. No hosting, no code, ready to use.

Professionals who connect Strava Social to LlamaIndex through Vinkius don't need to write code, manage servers, or worry about security. Everything is pre-configured, secure, and runs automatically in the background.

4,000+MCP Integrations
<40msResponse time
100%Fully managed
Raw MCP
Vinkius
Ready-to-use MCPsFind and configure each manually4,000+ MCPs ready to use
Connection SetupManual coding & server setup1-click instant connection
Server HostingYou host it yourself (needs 24/7 uptime)100% hosted & managed by Vinkius
Security & PrivacyStored in plaintext config filesBank-grade encrypted vault
Activity VisibilityBlind execution (no logs or tracking)Live dashboard with real-time logs
Cost ControlRunaway AI token spend riskAutomatic budget limits
Revoking AccessMust delete files or code to stop1-click disconnect button
The Vinkius Advantage

How Vinkius secures Strava Social for LlamaIndex

Every request between LlamaIndex and Strava Social is protected by our secure gateway. We automatically keep your sensitive data private, prevent unauthorized access, and let you disconnect instantly at any time.

< 40msCold start
Ed25519Signed audit chain
60%Token savings
FAQ

Frequently asked questions

01

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.

02

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).

03

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.

04

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

05

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Strava Social tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.

06

Does LlamaIndex support async MCP calls?

Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.

07

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

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