Mi Fitness MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_connection_statusC | Check connection status |
| sync_dataC | Synchronize Mi Fitness data |
| get_profileB | Get user profile information |
| get_daily_summaryC | Get daily activity summary |
| query_metric_seriesD | Query metric series |
| query_heart_rateC | Query heart rate samples |
| query_body_measurementsD | Query body measurements |
| query_workoutsC | Query official Xiaomi workout sessions |
| summarize_workoutsB | Summarize workout volume by sport or ISO week |
| get_workout_recordsC | Get personal workout records for a date range |
| compare_workout_periodsC | Compare workout totals between two date ranges |
| get_data_coverageD | Get data coverage |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 12 tools
Most tools are clearly distinct, but `get_workout_records` vs `query_workouts` could be confused (personal vs official workouts). Also `query_metric_series` is somewhat generic and may overlap with `query_heart_rate` and `query_body_measurements`.
All tool names follow a verb_noun structure, but there is a mix of `get_` and `query_` prefixes (both meaning retrieval). This is a minor deviation from a perfectly uniform pattern.
12 tools is well within the ideal 3-15 range and each tool serves a distinct purpose for a fitness data server, covering connection, sync, profile, summaries, metrics, workouts, and data coverage.
The toolset offers broad coverage for retrieving and analyzing fitness data, including raw series, summaries, workouts, and comparisons. Minor gaps could include sleep tracking or goal management, but they are not obviously required for the stated purpose.