Strava Planning MCP Server for Vercel AI SDK 14 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Strava Planning 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.
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 Planning, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* 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 Planning MCP Server
Connect Strava Planning to any AI agent and manage your training logistics — route creation, GPX/TCX export, manual activity logging, gear tracking, segment favoriting, and profile management.
The Vercel AI SDK gives every Strava Planning tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 14 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
- Route Management — List, view, and analyze all your saved routes with distance, elevation, and descriptions
- Route Streams — Get GPS coordinates, elevation profiles, and distance data for any route
- Route Export — Export routes to GPX and TCX formats for GPS devices (Garmin, Wahoo, etc.)
- Manual Activity Creation — Log activities not recorded by Strava (gym, yoga, cross-training) with full details
- Activity Updates — Edit activity names, descriptions, assign gear, mark commutes or indoor sessions
- File Uploads — Upload FIT, TCX, or GPX files for processing by Strava with status tracking
- Segment Management — Star (favorite) or unstar segments for quick training access
- Athlete Profile — View and update your profile information including weight for accurate power-to-weight ratios
- Athlete Zones — Review your heart rate and power zone configurations
- Gear Details — Track equipment mileage, models, and primary gear assignments
The Strava Planning MCP Server exposes 14 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 Planning to Vercel AI SDK via MCP
Follow these steps to integrate the Strava Planning 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 14 tools from Strava Planning and passes them to the LLM
Why Use Vercel AI SDK with the Strava Planning MCP Server
Vercel AI SDK provides unique advantages when paired with Strava Planning 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 Planning integration everywhere
Built-in streaming UI primitives let you display Strava Planning 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 Planning + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Strava Planning MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Strava Planning in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Strava Planning tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Strava Planning capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Strava Planning through natural language queries
Strava Planning MCP Tools for Vercel AI SDK (14)
These 14 tools become available when you connect Strava Planning to Vercel AI SDK via MCP:
create_activity
Required: name (activity name), type (activity type like "Run", "Ride", "Swim", "Walk", "Hike"), startDate (ISO 8601 format), elapsedTime (seconds). Optional: description, distance (meters). Use this to log activities recorded outside of Strava (gym workouts, yoga, cross-training, etc.). Activity types must match Strava's valid types list. Create a manual activity in Strava
export_route_gpx
GPX files can be downloaded and loaded onto GPS devices (Garmin, Wahoo, etc.) for navigation. The routeId is from Strava route URLs. Use this to export routes to your GPS device for guided training. Get the GPX export URL for a Strava route
export_route_tcx
TCX files include route data with additional training metadata. Compatible with Garmin Training Center and other fitness platforms. Use this to export routes with training metadata. Get the TCX export URL for a Strava route
get_athlete
Use this to review personal profile details, check equipment assignments, or verify account settings. Get the authenticated athlete's profile information
get_athlete_zones
Required for zone-based training analysis. Use this to review training zones, ensure zones are correctly set, or use zone data for activity analysis. Get the athlete's custom heart rate and power zones
get_gear
The gearId is found in activity data or athlete profile. Use this to check equipment mileage for maintenance planning or to analyze performance with specific gear. Get details about a piece of equipment (bike, shoes) tracked in Strava
get_route
The routeId is found in Strava route URLs. Use this to review route characteristics before training or to plan similar routes. Get detailed information about a specific Strava route
get_route_streams
The "types" parameter is comma-separated: "latlng", "altitude", "distance". Use this to preview a route's elevation profile, understand the terrain, or export GPS data for navigation. Get elevation and GPS data streams for a Strava route
get_upload_status
Status values: "Your activity is ready" (success), "Your activity is still processing" (wait and retry), or error messages. The uploadId is returned by upload_activity. Poll this endpoint every 5-10 seconds after upload until ready. Check the status of a Strava activity upload
list_routes
Each route includes: name, distance, elevation gain, type (ride/run), description, and whether it's private. Use this to review saved routes, plan upcoming workouts, or export route data for GPS devices. List all routes created by the authenticated athlete
star_segment
Set starred=true to favorite, starred=false to unfavorite. The segmentId is from Strava segment URLs. Use this to manage your favorite segments for quick access and training focus. Star (favorite) or unstar a Strava segment
update_activity
The activityId is the numeric ID. Updatable fields: name, description, sport_type, gear_id (to assign equipment), commute (mark as commute: "true"/"false"), trainer (mark as indoor: "true"/"false"). Use this to correct activity details, assign gear, or add descriptions after the fact. Update an existing Strava activity
update_athlete
Currently only "weight" (in kg) is supported by the API. Accurate weight is important for power-to-weight ratio calculations and performance analysis. Use this when your weight changes to keep performance metrics accurate. Update the authenticated athlete's profile information
upload_activity
Supported data_type: "fit", "fit.gz", "tcx", "tcx.gz", "gpx", "gpx.gz". Returns an upload ID to check status with get_upload_status. Note: Actual file upload requires multipart/form-data with the file content. This endpoint initiates the process. Check upload status periodically — processing takes 10-60 seconds. Upload an activity file (FIT, TCX, GPX) to Strava for processing
Example Prompts for Strava Planning in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Strava Planning immediately.
"List all my saved routes."
"Export route 12345 to GPX format."
"Create a manual activity for today's gym session."
Troubleshooting Strava Planning MCP Server with Vercel AI SDK
Common issues when connecting Strava Planning to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpStrava Planning + Vercel AI SDK FAQ
Common questions about integrating Strava Planning MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect Strava Planning with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
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 Planning to Vercel AI SDK
Get your token, paste the configuration, and start using 14 tools in under 2 minutes. No API key management needed.