Mirobody
Lab results to LOINC codes and UCUM units, symptoms and diagnoses to ICPC-3. Offline, no API key.
Description from the maker (original English)
Read-only access to your own Mi Fitness (Xiaomi) data: sleep, heart rate, steps, workouts
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"mifit": {
"command": "uvx",
"args": [
"mifit",
"mcp"
]
}
}
}Run this in your terminal
claude mcp add mifit -- uvx mifit mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"mifit": {
"command": "uvx",
"args": [
"mifit",
"mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"mifit": {
"type": "stdio",
"command": "uvx",
"args": [
"mifit",
"mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account Jenwein, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.4.0) reached the registry 9 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: Mirobody, FHIR MCP Server, Google Health MCP
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Lab results to LOINC codes and UCUM units, symptoms and diagnoses to ICPC-3. Offline, no API key.
MCP server providing seamless access to FHIR APIs for AI tools and healthcare applications
Privacy-first unofficial Google Health API v4 MCP server for health, sleep, activity, HR agents
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
Read your own Mi Fitness (小米运动健康) data from the Xiaomi cloud: a small Python library, a command-line tool and an MCP server for AI assistants.
The Mi Fitness app syncs your steps, heart rate, sleep and more to the Xiaomi cloud, but Xiaomi offers no public API for individuals. mifit signs in to your own account by QR code, reads that synced data and returns it as JSON or as Python objects, so you can build on it.
Unofficial. Not affiliated with, endorsed by or supported by Xiaomi.
See Disclaimer.
| Domain | What you get | records type | Checked against the app |
|---|---|---|---|
steps | steps and distance per day | StepRecord | yes |
heart_rate | raw heart-rate samples | HeartRatePoint | yes |
heart_rate_daily | heart rate per day: average, maximum, minimum, resting | HeartRateDailySummary | yes |
consumption | calories per day: resting, active, intake, total | ConsumptionRecord | yes |
sleep | sleep per day: totals, stage minutes, sessions with their stage timeline | SleepRecord → SleepSession → SleepStage | yes; the sleep score could not be checked and is in raw only |
workouts | one entry per workout: start and end, sport, duration, distance, active and total calories, average and maximum heart rate, steps | Workout | yes |
workout_detail | per workout (outdoor runs and rides): per-second samples (heart rate, cumulative distance and steps, cadence, pace or speed) and the GPS track | WorkoutDetail → WorkoutSample / TrackPoint | yes (one outdoor run, one ride); altitude is in raw only: the run's was a few metres off the app's |
spo2_daily | blood oxygen (SpO2) per day: average, maximum, minimum | Spo2DailySummary | yes |
spo2 | raw SpO2 readings | Spo2Point | yes |
stress_daily | stress level per day: average, highest, lowest, and minutes in each stress band (relaxed, mild, moderate, severe) | StressDailySummary | yes |
activity_daily | activity per day, as on the app's 活力指标 page: activity count (活动次数), activity minutes (活动时长), active calories (卡路里) | ActivityDailySummary | yes |
weight | weight entries: time, weight, BMI (body composition in raw only) | WeightRecord | yes; body composition could not be checked and is in raw only |
profile (its own command: mifit profile) | height, weight, daily step, calorie and activity-time goals | UserProfile | yes |
raw (CLI: mifit raw; Python: client.raw, raw_window, daily_report) | the rows of any fitness-data or daily-report key, as the service sends them | none: the service's rows, uninterpreted | not applicable: nothing is interpreted |
"Checked against the app" means the values were compared with what the Mi Fitness app shows, on one real account (China region, UTC+8). More is planned. Meanwhile, mifit raw (in Python raw_window and daily_report) returns the rows of any other key of the fitness-data or (with --daily) daily-report endpoint, uninterpreted.
What changed in each version, breaking changes included, is in CHANGELOG.md.
Requires Python 3.12 or later; uv installs one for you if needed.
uv tool install mifit # recommended: its own environment, `mifit` on your PATH
pipx install mifit # the same, with pipx pip install mifit # into the current environment, to use it as a library
Upgrade: uv tool upgrade mifit (or pipx upgrade mifit, pip install -U mifit).
mifit login
A QR code is drawn in the terminal, with the login URL below it. Scan it with the Xiaomi / Mi Fitness app on your phone (or open the URL) and approve the sign-in. Your password never passes through mifit.
The session is saved to ~/.mifit/session.json (on Windows %USERPROFILE%\.mifit\session.json). It grants access to your Mi Fitness account's health data (not only reading). It also holds your account's passToken, which mifit uses to renew the session when it expires. The passToken is account-level: it can obtain tokens for any Xiaomi service, so the file grants access to your whole Xiaomi account, not just your Mi Fitness health data, and it stays useful long after the session token itself has expired. Treat it like a password, and do not share it or commit it. On Linux and macOS the file is readable by you only; on Windows it relies on your user profile's permissions.
If Xiaomi asks for an extra security confirmation, mifit login prints a URL: open it, confirm, then run mifit login again.
mifit mcp is a Model Context Protocol server: AI assistants such as Claude Desktop, Claude Code, Cursor and VS Code start it on your computer and read your Mi Fitness data when you ask them about it ("how did I sleep last week?").
What leaves your computer. The results of the tools the assistant calls are sent to the assistant's model provider, like the rest of the conversation. The login stays in ~/.mifit on this computer: the server runs locally on stdin/stdout, opens no network port, never puts a credential in a result, and only reads your health data (the login tools save the new session to ~/.mifit). GPS tracks are off: the server gives a workout's route only when it was started with --allow-gps (in the Claude Desktop extension: when its Allow GPS tracks switch is on) *and* the assistant asks for it, and a route shows where you were, including where you live. (To serve assistants on other machines instead, see Remote access (HTTP): that server does open a port.)
Log in once, in a terminal:
uvx mifit login
(or mifit login after uv tool install mifit). Without a terminal, ask the assistant to log you in: it calls login_start, which returns the QR code to scan with the Xiaomi or Mi Fitness app.
Add the server to your assistant. uvx (part of uv) downloads and runs mifit when needed:
claude mcp add --scope user mifit -- uvx mifit mcp
// Claude Desktop: %APPDATA%\Claude\claude_desktop_config.json
// (macOS: ~/Library/Application Support/Claude/claude_desktop_config.json) {"mcpServers": {"mifit": {"command": "uvx", "args": ["mifit", "mcp"]}}}
// Cursor: ~/.cursor/mcp.json {"mcpServers": {"mifit": {"type": "stdio", "command": "uvx", "args": ["mifit", "mcp"]}}}
// VS Code: .vscode/mcp.json {"servers": {"mifit": {"command": "uvx", "args": ["mifit", "mcp"]}}}
After uv tool install mifit, the command can be mifit with the argument mcp instead. To allow GPS tracks, add --allow-gps after mcp (["mifit", "mcp", "--allow-gps"]).
mifit is also listed in the official MCP Registry as io.github.Jenwein/mifit, for clients that install servers from it.
Claude Desktop, in one click. Download mifit- .mcpb from the latest release and open it (or install it from Claude Desktop's Settings → Extensions): Claude Desktop (Windows, macOS) offers to install the extension. Its settings have an Allow GPS tracks switch, off by default. The extension runs the mifit release it came with: to update, install the .mcpb of the new release. Use either the extension or the JSON config above, not both.
Tools. Each reads one kind of data; dates are local calendar days.
| Tool | What it reads | Per call |
|---|---|---|
get_status | today's date, the time zone, the login state, the GPS setting (nothing from the cloud) | — |
get_steps | steps and distance per day | 92 days |
get_calories | calories per day: resting, active, intake, total | 31 days |
get_activity | activity count, minutes and calories per day | 92 days |
get_heart_rate_daily | heart rate per day: average, maximum, minimum, resting | 92 days |
get_sleep | sleep per day with its sessions; stage timelines on request | 92 days (7 with stages) |
get_spo2_daily | blood oxygen per day | 92 days |
get_stress_daily | stress level per day and the minutes in each stress band | 92 days |
get_weight | weighings | 92 days |
get_workouts | workouts | 92 days |
get_heart_rate | heart-rate samples, in buckets beyond 500 | 7 days |
get_spo2 | blood-oxygen readings, in buckets beyond 500 | 7 days |
get_workout_detail | one workout's per-second samples (outdoor runs and rides), and its GPS track with --allow-gps (the extension: with Allow GPS tracks on) | one workout, ≤ 500 rows |
get_profile | height, weight and daily goals | — |
login_start | log in by QR code (returns the code) | — |
login_status | how that login stands | — |
Results are the records of the Python API with local times (2026-10-07T23:12:00+08:00) instead of Unix seconds, never raw. Dense data is cut down to at most 500 rows and the notes say how. A result is kept for five minutes, so asking again sends no new requests.
Ask in your own words; the assistant picks the tools. For example: "Did my resting heart rate go up this month?"
mifit mcp --transport http runs the same server as a long-running service on streamable HTTP, so assistants on other machines can use it. Run it on the machine that keeps the login, such as a home server on your Tailscale or Headscale tailnet:
uv tool install mifit
mifit login # once, on the server: the session is saved in the server's ~/.mifit mifit mcp --transport http --host 100.64.0.5 --port 8766 --allowed-host mifit.ts.internal:8766
--host ADDRESS: the address to listen on. The default, 127.0.0.1, serves this machine only; give the server's tailnet address to serve the tailnet. 0.0.0.0 listens on every interface.--port PORT: default 8766. --path PATH: the endpoint, default /mcp.--allowed-host HOST[:PORT]: a Host header to accept. The server answers only requests whose Host header it knows, and refuses the others with HTTP 421 (the MCP SDK's DNS rebinding protection, always on). It knows 127.0.0.1, localhost and [::1] (any port) when it listens on loopback or on every interface, and its --host address with the port otherwise. Add each name the clients connect by, as they send it: mifit.ts.internal:8766, or mifit.ts.internal:* for any port. Repeat the option for more names.--allow-gps works as it does on stdio.Dates and local times are counted in the server's time zone. If it is not yours, start the server with yours, such as TZ=Asia/Shanghai (in the systemd unit below, its Environment= line).
At startup the server prints its URL and the Host headers it accepts on standard error. Then add it to each assistant by its URL:
claude mcp add --scope user --transport http mifit http://mifit.ts.internal:8766/mcp
codex mcp add mifit --url http://mifit.ts.internal:8766/mcp
Other clients take the URL as a streamable HTTP (http) server. To log in without a terminal on the server, ask the assistant: login_start returns the QR code in the tool result, nothing opens on the server's screen, and the session is saved on the server. If Xiaomi asks for a security confirmation, run mifit login in a terminal on the server (over SSH, say) and follow it.
Security. The HTTP server has no authentication. Anyone who can reach its port can read your Mi Fitness data through it, and can start a login that replaces you
Only the beginning is shown; read the rest in the repo