Strava Training MCP Server for Claude Code 12 tools — connect in under 2 minutes
Claude Code is Anthropic's agentic CLI for terminal-first development. Add Strava Training as an MCP server in one command and Claude Code will discover every tool at runtime. ideal for automation pipelines, CI/CD integration, and headless workflows via Vinkius.
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Vinkius Desktop App
The modern way to manage MCP Servers — no config files, no terminal commands. Install Strava Training and 2,500+ MCP Servers from a single visual interface.
# Your Vinkius token. get it at cloud.vinkius.com
claude mcp add strava-training --transport http "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
* 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 Training MCP Server
Connect Strava Training to any AI agent and unlock deep performance analysis from your Strava data — activity details, time-series streams, heart rate/power zones, segment efforts, lap splits, and lifetime athlete statistics.
Claude Code registers Strava Training as an MCP server in a single terminal command. Once connected, Claude Code discovers all 12 tools at runtime and can call them headlessly. ideal for CI/CD pipelines, cron jobs, and automated workflows where Strava Training data drives decisions without human intervention.
What you can do
- Activity Details — Full metrics: distance, time, elevation, HR, power, speed, weather, gear
- Activity Streams — Raw GPS, heart rate, power, cadence, altitude, speed, temperature, grade data
- Activity Zones — Heart rate and power zone distribution for training intensity analysis
- Activity Laps — Auto-split lap data with pace, distance, and elevation per split
- Segment Efforts — Find, compare, and analyze all efforts on any segment with detailed metrics
- Segment Streams — Elevation and grade profiles along segments for previewing difficulty
- Segment Details — Distance, elevation, grade, effort count, and personal records
- Athlete Statistics — Lifetime and recent totals for runs, rides, and all activities
- Athlete Zones — Personal heart rate and power zone configurations
- Gear Tracking — Equipment mileage, models, and primary gear assignments
The Strava Training MCP Server exposes 12 tools through the Vinkius. Connect it to Claude Code 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 Training to Claude Code via MCP
Follow these steps to integrate the Strava Training MCP Server with Claude Code.
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
Add the MCP Server
Run the command above in your terminal
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
Start using Strava Training
Ask Claude: "Using Strava Training, show me...". 12 tools are ready
Why Use Claude Code with the Strava Training MCP Server
Claude Code provides unique advantages when paired with Strava Training through the Model Context Protocol.
Single-command setup: `claude mcp add` registers the server instantly. no config files to edit or applications to restart
Terminal-native workflow means MCP tools integrate seamlessly into shell scripts, CI/CD pipelines, and automated DevOps tasks
Claude Code runs headlessly, enabling unattended batch processing using Strava Training tools in cron jobs or deployment scripts
Built by the same team that created the MCP protocol, ensuring first-class compatibility and the fastest adoption of new protocol features
Strava Training + Claude Code Use Cases
Practical scenarios where Claude Code combined with the Strava Training MCP Server delivers measurable value.
CI/CD integration: embed Strava Training tool calls in your deployment pipeline to validate configurations or fetch secrets before shipping
Headless batch processing: schedule Claude Code to query Strava Training nightly and generate reports without human intervention
Shell scripting: pipe Strava Training outputs into other CLI tools for data transformation, filtering, and aggregation
Infrastructure monitoring: run Claude Code in a cron job to query Strava Training status endpoints and alert on anomalies
Strava Training MCP Tools for Claude Code (12)
These 12 tools become available when you connect Strava Training to Claude Code via MCP:
get_activity
The activityId is the numeric ID from Strava activity URLs (e.g., strava.com/activities/12345678 → 12345678). Use this for deep analysis of any workout, ride, or run. Get detailed information about a specific Strava activity
get_activity_laps
Each lap includes distance, moving time, average speed, elevation gain, and pace. GPS devices and Strava auto-split activities into laps (typically ~1km or ~1mi). Use this to analyze pace consistency, identify fast/slow sections, and compare splits within a single activity. Get lap/split data for a Strava activity
get_activity_streams
The "types" parameter is comma-separated stream types: "time", "distance", "latlng", "altitude", "velocity_smooth", "heartrate", "cadence", "watts", "temp", "moving", "grade_smooth". Example: "heartrate,watts,velocity_smooth" for HR, power, and speed data. Each stream returns an array of values with corresponding timestamps. Use this for detailed performance analysis, visualization, or export. Get raw time-series data streams from a Strava activity (GPS, heart rate, power, cadence, altitude, speed, etc)
get_activity_zones
Requires activity ID. This data helps understand training intensity and whether the workout targeted the correct zones. Only available for activities with heart rate or power data. Summit/subscription feature. Get heart rate and power zone distribution for a Strava activity
get_athlete_stats
Use the athlete's Strava numeric ID. Returns recent_run_totals, recent_ride_totals, all_run_totals, all_ride_totals. Great for performance overview and progress tracking. Get consolidated activity statistics for any Strava athlete
get_athlete_zones
Requires profile:read_all scope. Use this to understand training zones for zone-based analysis of activities and efforts. Get the authenticated athlete's custom heart rate and power zones
get_gear
The gear ID is found in activity data or athlete profile. Use this to track equipment mileage, plan maintenance, or analyze performance with specific gear. Get details about a piece of equipment (bike, shoes) tracked in Strava
get_segment
The segment ID is found in Strava segment URLs. Use this to discover segment characteristics before attempting it or to compare segments. Get details of a Strava segment including distance, elevation, grade, and leaderboards
get_segment_effort
Includes elapsed time, distance, average speed, heart rate, power, start date, and activity reference. The effort ID is found in segment effort listings or activity details. Use this to analyze specific KOM/QOM attempts and compare efforts on the same segment. Get details of a specific segment effort (KOM/QOM/PR attempt)
get_segment_effort_streams
Same format as activity streams but limited to the segment portion. The "types" parameter is comma-separated: "time", "distance", "latlng", "altitude", "velocity_smooth", "heartrate", "cadence", "watts". Use this for granular analysis of segment performance. Get time-series data streams for a specific segment effort
get_segment_streams
Useful for previewing a segment's difficulty profile before attempting it. The "types" parameter accepts "distance", "altitude", "grade_smooth". Use this to understand elevation changes and steepness patterns along a segment. Get time-series data streams for a Strava segment (elevation profile, grade, etc)
list_segment_efforts
Filter by athlete_id (required), optionally segment_id to get efforts on a specific segment, and date range with start_date_local and end_date_local (ISO 8601 format). Use this to find PRs, analyze progress on segments over time, or compare multiple efforts on the same segment. List all segment efforts for an athlete, optionally filtered by segment and date range
Example Prompts for Strava Training in Claude Code
Ready-to-use prompts you can give your Claude Code agent to start working with Strava Training immediately.
"Show my athlete statistics."
"Get activity streams for activity 12345678 with heart rate, power, and speed."
"Show my segment efforts on segment 22978."
Troubleshooting Strava Training MCP Server with Claude Code
Common issues when connecting Strava Training to Claude Code through the Vinkius, and how to resolve them.
Command not found: claude
npm install -g @anthropic-ai/claude-codeConnection timeout
Strava Training + Claude Code FAQ
Common questions about integrating Strava Training MCP Server with Claude Code.
How do I add an MCP server to Claude Code?
claude mcp add --transport http "" in your terminal. Claude Code registers the server and discovers all tools immediately.Can Claude Code run MCP tools in headless mode?
How do I list all connected MCP servers?
claude mcp in your terminal to see all registered servers and their status, or type /mcp inside an active Claude Code session.Connect Strava Training with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Strava Training to Claude Code
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.