mifit

mifit

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.

What it reads today

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.

Install

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).

Log in

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.

Use with an AI assistant (MCP)

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.

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-<version>.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?"

Export

mifit export <domain> --from YYYY-MM-DD --to YYYY-MM-DD [--json PATH] [--full] [--no-track] [--chunk day|week|month] [--long] [--resume]

• <domain>: activity_daily, consumption, heart_rate, heart_rate_daily, sleep, spo2, spo2_daily, steps, stress_daily, weight, workouts or workout_detail (per-second samples and GPS track of outdoor runs and rides).
• --from / --to: first and last day, inclusive, as local calendar days.
• --json PATH: write to a file instead of standard output.
• --full: heart_rate only; page backwards through the history instead of querying one time window (see Known limitations). This is a single read: it ignores --from, so it needs no --long however long the range, and it cannot be combined with --chunk, --long or --resume.
• --no-track: workout_detail only; skip the GPS file, so no track is requested or written.
• --chunk day|week|month: the chunk size (1, 7 or 31 days) for a range longer than one chunk; the default depends on the domain.
• --long: allow a range over 92 days.
• --resume: continue an interrupted export from PATH.partial (needs --json).

mifit export sleep --from 2026-10-01 --to 2026-10-07 --json sleep.json

The output is one JSON object with three lists:

{ "records": [], "raw": [], "notes": [] }

Long ranges

A range longer than one chunk (7 days for raw heart rate, SpO2 and workout detail, 31 days for everything else, counted from --from) is read chunk by chunk, one request at a time, with progress on standard error. A shorter range is a single read, as before. The chunks are merged into one output of the same shape; with more than one chunk, each note starts with the chunk it came from. Ranges over 92 days need --long: they take many requests and can run for many minutes. The one exception is heart_rate --full: it ignores --from and is a single read, never chunked, so it needs no --long.

mifit export heart_rate --from 2026-01-01 --to 2026-06-30 --long --json heart_rate.json

With --json PATH, progress is kept in PATH.partial: your exported data plus the export's arguments (domain, dates, chunk size), no credentials. Treat it like the output itself. If the export stops (a network error, an expired session, Ctrl+C), the finished chunks stay in that file; rerun the same command with --resume and only the missing chunks are read. The output is the same as an uninterrupted run's, and the partial file is deleted once it is written. An export to standard output is chunked the same way but cannot be resumed.

A failed chunk stops the export; nothing is retried automatically. If one chunk keeps failing, you can skip it by exporting the ranges before and after it separately.

Any key: mifit raw

mifit raw <key> --from YYYY-MM-DD --to YYYY-MM-DD [--daily [--tag TAG]] [--json PATH] [--long]

Reads any key of the fitness-data or (with --daily) daily-report endpoint as the service sends it, whether or not mifit also has a domain for it (heart_rate has one):

• It writes {records: [], raw, notes}. raw holds the service's rows, with their own fields and value decoded from its JSON string; records is always empty.
• For a raw key it asks the service a day early and keeps the rows inside your window, so the first hours of the window are complete.
• --daily reads the key's daily report instead, one row per local day that has data; --tag TAG picks another aggregated tag (default daily_report).
• It is one read, paged: a range over 92 days needs --long, and there is no --resume.
• The keys known so far are listed in notes/domain-catalog.md.

mifit raw stress --from 2026-10-01 --to 2026-10-07 --json stress.json

Python API

from mifit import MiFit

client = MiFit()  # uses the session saved by `mifit login`

steps = client.steps("2026-10-01", "2026-10-07")
for day in steps.records:
    print(day.date, day.steps, day.distance_m)

sleep = client.sleep("2026-10-01", "2026-10-07")
energy = client.consumption("2026-10-01", "2026-10-07")
heart = client.heart_rate("2026-10-07", "2026-10-07")      # one time window
heart_full = client.heart_rate("2026-10-07", "2026-10-07", full=True)

detail = client.workout_detail("2026-10-12", "2026-10-12")  # samples and GPS track
no_gps = client.workout_detail("2026-10-12", "2026-10-12", track=False)

rows = client.raw("sleep", "2026-10-07", "2026-10-07")     # any fitness-data key, as served
window = client.raw_window("stress", "2026-10-07", "2026-10-07")        # a complete window
daily = client.daily_report("valid_stand", "2026-10-01", "2026-10-07")  # daily rows

raw_window(key, ...) is raw made complete: it asks a day early and keeps the rows of your window, with value decoded. daily_report(key, ...) returns the key's daily rows, one per local day that has data, with tag= to pick a tag other than daily_report. Both give records=[] and the rows in raw.

Which keys exist and what is verified: notes/domain-catalog.md.

workout_detail gives one WorkoutDetail per workout in records: its workout summary (the Workout of workouts), its samples (WorkoutSample, one per recorded second) and its track (TrackPoint); track=False asks for no GPS file.

Dates are "YYYY-MM-DD" strings (local calendar days, inclusive) or ints of Unix seconds. Each domain method returns a result with records, raw and notes; raw(key, ...) returns the service's rows as they came, for any key of the fitness-data endpoint (data/get_fitness_data_by_time), not the daily reports (see raw_window for a complete window). Errors specific to mifit derive from mifit.MiFitError: AuthError (no usable session, or HTTP 401), its subclass RenewalError (an HTTP 401 the automatic renewal could not fix; log in again), ApiError (the service refused the request or sent something unreadable) and NotificationRequiredError (raised by the login when Xiaomi asks for a security confirmation). Network failures surface as requests exceptions, and a bad date argument raises ValueError or TypeError.

For a long range, read_chunks reads one chunk at a time (the CLI's chunk sizes; size="day", "week" or "month" overrides them) and merge_chunks joins the parts. Its dates are "YYYY-MM-DD" strings only.

from mifit.chunks import merge_chunks

parts = []
for chunk, part in client.read_chunks("heart_rate", "2026-01-01", "2026-06-30"):
    print(chunk.label, len(part.records))  # each chunk is read when the loop asks for it
    parts.append((chunk, part))
heart = merge_chunks(parts)  # its records are those of one read of the whole range

read_chunks(..., skip=labels) passes over the chunks whose labels you already have, to resume, and options= gives keyword arguments to every chunk's call, such as {"track": False} for workout_detail. options={"full": True} is refused with ValueError: a full read pages back from each chunk's end, so every chunk would read the same samples again; call heart_rate(..., full=True) once instead. The library has no 92-day limit: a long range is many requests, so ask for what you need.

When a request is refused with HTTP 401, the client renews the session once from its passToken and sends the request again. A client that uses the session saved by mifit login saves the renewed session back to ~/.mifit. Explicit sessions (MiFit(session)) are renewed in memory; read client.session to keep the renewed one. MiFit(auto_renew=False) turns renewal off, so a 401 raises AuthError straight away.

MiFit(http=...) injects the HTTP client, to keep a client offline. With renewal on, the renewal runs on that client too, so its get must accept the cookies= and allow_redirects= keywords as well as the usual params=, headers= and timeout= (a requests.Session does). Without an injected client, the renewal uses a fresh requests.Session of its own.

Two layers: raw and records

• raw is the service's decoded payloads (the inner value of each row, or for consumption the response's result object; for workout_detail, each workout's decoded summary and files as stored values), with Xiaomi's own field names. It is not a complete dump of every row the service sent. The generic reads are the exception: for raw_window, daily_report and mifit raw, raw holds each whole row the service sent for your window, its outer fields included and its value decoded.
• records are typed dataclasses with neutral names (asleep_min, avg_hr_bpm, ...). A field's meaning is established from what the app displays or from the app's own code before it enters this layer. One, the REM stage, rests on the app's code alone, because the author's device reports no REM. The sleep score is not in this layer: the app showed only a rating, so the number could not be checked; it is in raw as sleep_score. A value the service did not report is None, never a made-up 0.
• notes are caveats about that particular result: skipped rows, data that may be incomplete.

Known limitations

• Cloud only, and the cloud lags. mifit reads what the app has synced to the Xiaomi cloud. If cloud sync is off or has not run yet, data is missing or late; the latest day may be partial.
• The calorie ring is synthesized by the app. The app combines cloud activity with phone-side activity, so consumption for the latest day can read lower than the ring. step_calories in steps is the step report's walking-calorie figure, not the ring.
• Raw windows are corrected by the SDK. The service drops the samples at the start of a raw-data window (the first bucket); every dense raw key checked does this: heart_rate, spo2, stress and calories (notes/08, notes/11, notes/domain-catalog.md). The heart_rate, spo2 and weight reads, raw_window and mifit raw ask the service for a day before the start and keep only the requested window. raw(key, ...) returns the service's answer as it came, for any key, without this correction: use raw_window for a complete window. --full (full=True, heart_rate only) pages backwards from the end date instead; it ignores the start date and stops after 10 pages, saying so in notes when older data remains.
• NaN and Infinity become null. JSON has no such numbers, so where the service sends one, the CLI writes null and a note says how many it replaced.
• A read the service breaks off says so. When the service reports more pages but sends no usable cursor to fetch them, the read stops there and notes says that rows in the range may be missing.
• Workout detail reads outdoor runs and rides only. It covers the file formats seen so far (record file versions 8 and 5, GPS file version 2). Walks, hikes, swims, indoor runs and other sports, and other file versions, get a note and no samples: each needs a real file and a hand-written layout table first. Altitude is in raw only. One call reads the detail of at most 10 workouts (long ranges are read a week per chunk). A GPS track shows where you were, including where you live: --no-track (track=False) leaves it out. The download links and keys never appear in the output.
• Workout files outside the China region are untested. Files download only from hosts under .fds.api.xiaomi.com, the host seen on a China-region account. A link to another host is refused with a note, and that workout keeps its summary without samples or track.
• Read-only. mifit never writes, changes or deletes anything in your account.
• Sessions expire. On an HTTP 401, mifit renews the session once from the stored passToken and retries the request. When that fails, or the session was saved before renewal existed (it has no passToken), run mifit login again. Renewal was checked live on 2026-10-15. The lifetime without renewal is still being observed and is at least 22 hours so far: logins, 401s and renewals are logged (event, time and ages only) to ~/.mifit/session-log.jsonl. (An HTTP 401 can also mean the request signature was refused; a 401 right after a renewal is taken to mean that and is not retried.)
• Narrowly tested. One account in the China region. Other regions are routed but unverified, and Xiaomi can change the protocol at any time.
• Be gentle with the service. Requests are sent one at a time with about a second's pause plus random jitter. Long ranges are read in chunks, and a range over 92 days needs --long. This lowers the risk of being rate-limited, but does not remove it.

Development

git clone https://github.com/Jenwein/mifit.git
cd mifit
pip install -e ".[test]"
python -m pytest -q

The tests are offline: a fake transport stands in for the Xiaomi cloud, and any attempt to open a network connection fails the test. The test extra includes tzdata, so the daylight-saving tests also run on Windows, which has no time-zone database of its own. CI runs the suite on Linux with Python 3.12, 3.13 and 3.14.

Disclaimer

mifit is an independent, unofficial project. It is not affiliated with, endorsed by or supported by Xiaomi. "Xiaomi" and "Mi Fitness" are trademarks of their owners and are used here only to say what the software works with.

It is meant for reading your own data with your own account. Automated access may conflict with Xiaomi's terms of service and could get your account rate-limited or restricted; use it at your own risk. Nothing it outputs is medical advice. The software is provided "as is", without warranty of any kind (see LICENSE).

Credits

Request signing and encryption, the transport, the region table and the STS token exchange are adapted from Mi-Fitness-Sync by kevinkwee (MIT License). See THIRD_PARTY_NOTICES.

License

MIT. See LICENSE.