Fitbit MCP Server for Mastra AI 14 tools — connect in under 2 minutes
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Fitbit through Vinkius and Mastra agents discover all tools automatically. type-safe, streaming-ready, and deployable anywhere Node.js runs.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";
async function main() {
// Your Vinkius token. get it at cloud.vinkius.com
const mcpClient = await createMCPClient({
servers: {
"fitbit": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "Fitbit Agent",
instructions:
"You help users interact with Fitbit " +
"using 14 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with Fitbit?"
);
console.log(result.text);
}
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.
Mastra's agent abstraction provides a clean separation between LLM logic and Fitbit tool infrastructure. Connect 14 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.
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 Mastra AI 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 Mastra AI via MCP
Follow these steps to integrate the Fitbit MCP Server with Mastra AI.
Install dependencies
Run npm install @mastra/core @mastra/mcp @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.ts and run with npx tsx agent.ts
Explore tools
Mastra discovers 14 tools from Fitbit via MCP
Why Use Mastra AI with the Fitbit MCP Server
Mastra AI provides unique advantages when paired with Fitbit through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add Fitbit without touching business code
Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
TypeScript-native: full type inference for every Fitbit tool response with IDE autocomplete and compile-time checks
One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure
Fitbit + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the Fitbit MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query Fitbit, process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed Fitbit as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query Fitbit on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using Fitbit tools alongside other MCP servers
Fitbit MCP Tools for Mastra AI (14)
These 14 tools become available when you connect Fitbit to Mastra AI 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 Mastra AI
Ready-to-use prompts you can give your Mastra AI 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 Mastra AI
Common issues when connecting Fitbit to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpFitbit + Mastra AI FAQ
Common questions about integrating Fitbit MCP Server with Mastra AI.
How does Mastra AI connect to MCP servers?
MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.Can Mastra agents use tools from multiple servers?
Does Mastra support workflow orchestration?
Connect Fitbit with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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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 Mastra AI
Get your token, paste the configuration, and start using 14 tools in under 2 minutes. No API key management needed.