What data streams are available for activities?

Available streams include: time, distance, latlng (GPS coordinates), altitude, velocity_smooth (speed), heartrate, cadence, watts (power), temp (temperature), moving (moving flag), and grade_smooth (incline %). Request specific streams with comma-separated types, e.g., "heartrate,watts,velocity_smooth". Not all streams are available for every activity — it depends on the recording device.

What are activity zones and how are they calculated?

Activity zones show the time spent in each heart rate zone (Z1-Z5) or power zone during an activity. Zones are based on the athlete's personal zone configuration (set in Strava settings). Zone analysis reveals training intensity — whether a workout was aerobic (Z1-Z2), threshold (Z3), or anaerobic (Z4-Z5). This data requires a heart rate monitor or power meter.

How do I find my athlete ID on Strava?

Your athlete ID is the numeric portion of your Strava profile URL. For example, from https://www.strava.com/athletes/12345678, your athlete ID is 12345678. You can also get it from the get_athlete tool in the Strava Planning or Strava Social MCP servers.

Strava Training MCP Server for Vercel AI SDK 12 tools — connect in under 2 minutes

Name: Strava Training
Availability: InStock
Author: Vinkius

ai-sdk.dev/docs/ai-sdk-core/mcp

Built by Vinkius GDPR 12 Tools SDK

The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Strava Training through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.

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Vinkius supports streamable HTTP and SSE.

typescript

import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

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

  try {
    const tools = await mcpClient.tools();
    const { text } = await generateText({
      model: openai("gpt-4o"),
      tools,
      prompt: "Using Strava Training, list all available capabilities.",
    });
    console.log(text);
  } finally {
    await mcpClient.close();
  }
}

main();

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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.

The Vercel AI SDK gives every Strava Training tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 12 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.

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 Vercel AI SDK 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 Vercel AI SDK via MCP

Follow these steps to integrate the Strava Training MCP Server with Vercel AI SDK.

Install dependencies

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

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the script

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

Explore tools

The SDK discovers 12 tools from Strava Training and passes them to the LLM

Why Use Vercel AI SDK with the Strava Training MCP Server

Vercel AI SDK provides unique advantages when paired with Strava Training through the Model Context Protocol.

TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box

Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Strava Training integration everywhere

Built-in streaming UI primitives let you display Strava Training tool results progressively in React, Svelte, or Vue components

Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency

Strava Training + Vercel AI SDK Use Cases

Practical scenarios where Vercel AI SDK combined with the Strava Training MCP Server delivers measurable value.

AI-powered web apps: build dashboards that query Strava Training in real-time and stream results to the UI with zero loading states

API backends: create serverless endpoints that orchestrate Strava Training tools and return structured JSON responses to any frontend

Chatbots with tool use: embed Strava Training capabilities into conversational interfaces with streaming responses and tool call visibility

Internal tools: build admin panels where team members interact with Strava Training through natural language queries

Strava Training MCP Tools for Vercel AI SDK (12)

These 12 tools become available when you connect Strava Training to Vercel AI SDK 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 Vercel AI SDK

Ready-to-use prompts you can give your Vercel AI SDK 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 Vercel AI SDK

Common issues when connecting Strava Training to Vercel AI SDK through the Vinkius, and how to resolve them.

createMCPClient is not a function

Install: npm install @ai-sdk/mcp

Strava Training + Vercel AI SDK FAQ

Common questions about integrating Strava Training MCP Server with Vercel AI SDK.

How does the Vercel AI SDK connect to MCP servers?

Import createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.