Fitbit 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 Fitbit through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
ASK AI ABOUT THIS MCP SERVER
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 Fitbit, 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 Fitbit MCP Server
Connect your Fitbit account to any AI agent and gain instant access to your comprehensive health and fitness data through natural conversation.
The Vercel AI SDK gives every Fitbit 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
- Activity Tracking — Retrieve daily activity summaries including steps, distance, calories, and active minutes for any date
- Sleep Analysis — Access detailed sleep logs with stages (deep, light, REM, awake) for individual nights or time series trends
- Heart Rate Monitoring — Query resting heart rate, intraday zones, and historical cardiac trends
- SpO2 & Breathing — View blood oxygen saturation levels and breathing rate data
- Body Composition — Track weight measurements and cardio fitness scores over time
- Nutrition Logs — Access water intake and food logging data for dietary tracking
- Device Management — Check connected Fitbit devices and their sync status
The Fitbit 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 Fitbit to Vercel AI SDK via MCP
Follow these steps to integrate the Fitbit 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 Fitbit and passes them to the LLM
Why Use Vercel AI SDK with the Fitbit MCP Server
Vercel AI SDK provides unique advantages when paired with Fitbit 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 Fitbit integration everywhere
Built-in streaming UI primitives let you display Fitbit 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
Fitbit + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Fitbit MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Fitbit in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Fitbit tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Fitbit capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Fitbit through natural language queries
Fitbit MCP Tools for Vercel AI SDK (14)
These 14 tools become available when you connect Fitbit to Vercel AI SDK via MCP:
get_activities_date
Returns steps, calories burned, distance walked, active minutes, floors climbed, elevation and sedentary minutes. Date format: YYYY-MM-DD or "today". Get activity summary for a specific date
get_activities_timeseries
Resource paths: "steps", "calories", "distance", "floors", "elevation", "minutesSedentary", "minutesLightlyActive", "minutesFairlyActive", "minutesVeryActive", "activityCalories". Period: 1d, 7d, 30d, 1w, 1m, 3m, 6m, 1y, max or startDate/endDate (YYYY-MM-DD). Detail level: "1min", "5min", "15min", "1day" for intraday data. Get activity time series data over a date range
get_body_weight
Returns weight in kg, BMI, fat percentage and date logged. Date format: YYYY-MM-DD. Get body weight log entries for a specific date
get_breathing_rate
Returns breathing rate in breaths per minute. Available on Fitbit devices with SpO2 sensors. Date format: YYYY-MM-DD. Get breathing rate for a specific date
get_cardio_fitness_score
Returns VO2 Max values and percentile rankings. Date format: YYYY-MM-DD. Get cardio fitness score (VO2 Max) for a date range
get_devices
Returns device version, MAC address, battery level, last sync time and device type. Get all Fitbit devices connected to the user's account
get_foods_date
Returns total calories consumed, macros (carbs, protein, fat), water intake and list of logged foods with meal times. Date format: YYYY-MM-DD or "today". Get food log summary for a specific date
get_heart_date
Returns resting heart rate, heart rate zones (fat burn, cardio, peak, out of range) and calories burned in each zone. Date format: YYYY-MM-DD or "today". Get heart rate summary for a specific date
get_heart_timeseries
Returns resting heart rate and heart rate zones per day. Detail level: "1min", "5min", "15min", "1day" for intraday BPM data. Get heart rate time series data over a date range
get_profile
Returns display name, full name, age, height, weight, gender, locale, timezone, avatar URL and member since date. Get the authenticated user's Fitbit profile
get_sleep_date
Returns sleep start time, duration, minutes asleep, minutes awake, minutes in each sleep stage (light, deep, REM, awake), efficiency score and number of awakenings. Date format: YYYY-MM-DD or "today". Get sleep log for a specific date
get_sleep_timeseries
Returns daily sleep summaries with start time, duration, minutes asleep, efficiency and sleep stages. Date range format: startDate/endDate (YYYY-MM-DD). Get sleep log over a date range
get_spo2
Returns average SpO2 percentage and min/max values. Available on Fitbit devices with SpO2 sensors. Date format: YYYY-MM-DD. Get blood oxygen saturation (SpO2) for a specific date
get_water
Returns water consumption in milliliters and timestamps. Date format: YYYY-MM-DD. Get water intake log for a specific date
Example Prompts for Fitbit in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Fitbit immediately.
"How did I sleep last night?"
"Show my heart rate trends for the past week."
Troubleshooting Fitbit MCP Server with Vercel AI SDK
Common issues when connecting Fitbit to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpFitbit + Vercel AI SDK FAQ
Common questions about integrating Fitbit 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 Fitbit 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 Fitbit to Vercel AI SDK
Get your token, paste the configuration, and start using 14 tools in under 2 minutes. No API key management needed.