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 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. 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 |
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,workoutsorworkout_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_rateonly; 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--longhowever long the range, and it cannot be combined with--chunk,--longor--resume.--no-track:workout_detailonly; 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 fromPATH.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}.rawholds the service's rows, with their own fields andvaluedecoded from its JSON string;recordsis 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.
--dailyreads the key's daily report instead, one row per local day that has data;--tag TAGpicks another aggregated tag (defaultdaily_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
rawis the service's decoded payloads (the innervalueof each row, or for consumption the response'sresultobject; forworkout_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: forraw_window,daily_reportandmifit raw,rawholds each whole row the service sent for your window, its outer fields included and itsvaluedecoded.recordsare 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 inrawassleep_score. A value the service did not report isNone, never a made-up0.notesare 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
consumptionfor the latest day can read lower than the ring.step_caloriesinstepsis 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,stressandcalories(notes/08, notes/11, notes/domain-catalog.md). Theheart_rate,spo2andweightreads,raw_windowandmifit rawask 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: useraw_windowfor a complete window.--full(full=True,heart_rateonly) pages backwards from the end date instead; it ignores the start date and stops after 10 pages, saying so innoteswhen older data remains. - NaN and Infinity become
null. JSON has no such numbers, so where the service sends one, the CLI writesnulland 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
notessays 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
rawonly. 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 loginagain. 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.
Metadata
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|---|---|---|---|---|
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Total release size: 291.0 kB
Release files / mifit-0.3.1.tar.gz
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