FeelFit MCP Server
Provides access to body composition data from FeelFit smart scales, including measurements like weight, BMI, and body fat. Supports multi-account management and health goal tracking via the FeelFit Cloud API.
README
FeelFit MCP Server
MCP (Model Context Protocol) server for accessing body composition data from FeelFit smart scales. Supports multiple accounts.
Features
- Multi-account support
- Body composition measurements (weight, body fat, BMI, muscle mass, bone mass, water, protein, visceral fat, metabolic rate, body age)
- Device management (bound scales)
- Health goals
- Automatic authentication with token caching
Tools
| Tool | Description |
|---|---|
list_accounts |
List configured accounts and auth status |
login |
Authenticate account(s) |
get_profile |
Get user profile |
get_measurements |
Get all body composition measurements |
get_latest_measurement |
Get most recent measurement |
get_devices |
List bound smart scales |
get_goals |
Get health goals |
get_all_data |
Get complete data dump |
Setup
1. Install dependencies
pip install -r requirements.txt
2. Configure accounts
Create ~/.config/feelfit-mcp/config.json:
{
"accounts": [
{"email": "user@example.com", "password": "your_password"}
]
}
Or set the FEELFIT_CONFIG environment variable to a custom path.
3. Add to Claude Desktop / Claude Code
{
"mcpServers": {
"feelfit": {
"command": "python3",
"args": ["/path/to/mcp-feelfit/server.py"]
}
}
}
How it works
The server connects to the FeelFit Cloud API (feelfit.qnclouds.com) using the same protocol as the Android app. Passwords are encrypted with RSA before transmission. Authentication tokens are valid for 180 days.
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.