io.github.partymola/fitbit-mcp

Access Fitbit API data with OAuth, caching, and trend analysis via MCP.

Source

Official Registry

Updated

2026-10-01

// securityCaution

Runs locally
Official / curated
Open source
Community-trusted

Running security audit…

Credentials
Network egress
Code execution
Data access
Supply chain

// install

Copy the install command and let the AI configure it · recommended for beginners

Please install the "io.github.partymola/fitbit-mcp" MCP server from askskill:
Run: claude mcp add 'io-github-partymola-fitbit-mcp' -- npx -y fitbit-mcp

// use cases

Connect wearable data to an AI workflow

Developers can connect this MCP server to an MCP-compatible AI client so the model can access Fitbit Web API data directly. It fits scenarios where health or activity records need to be queried in conversation.

Run personal health trend analysis

Data analysts or researchers can use Fitbit data to inspect trends over time. It is suitable for analyzing time-series patterns such as steps and activity levels.

Reduce repeated requests and speed up queries

The local SQLite cache is useful when the same Fitbit data needs to be queried repeatedly. It can reduce repeated API access and improve follow-up analysis efficiency.

// docs

No documentation provided

Check the source repo for usage and examples.

Go to source repo ↗

// FAQ

What does this tool do?

This is an MCP server for the Fitbit Web API. It supports OAuth PKCE, a local SQLite cache, and trend analysis.

What prerequisites are needed before use?

Based on the description, you at least need access to the Fitbit Web API and authorization through OAuth PKCE. For exact setup details, see the source repository.

How is it different from calling the Fitbit API directly?

This tool adds an MCP interface, local SQLite caching, and trend analysis on top of the Fitbit Web API. For any additional abstractions or features, see the source repository.