zwift-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@zwift-mcpwhat's my training load this week?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
zwift-mcp
Your Zwift training history in a local SQLite database, exposed to MCP clients (Claude, and anything else that speaks MCP) and over a REST API.
Two components:
zwift_downloader.py— a cron job that pulls from the Zwift game API and from ZwiftPower, parses the original FIT files, and stores everything in SQLitemcp_server.py— a stateless streamable-HTTP MCP server plus a REST API, both reading the same database behind one bearer token
Why two sources
Zwift and ZwiftPower know different things, and neither is complete:
Zwift API | ZwiftPower | |
Every ride, including solo and workouts | ✅ | ❌ races only |
Heart rate, cadence, speed, max power | ✅ detail endpoint | ✅ per race |
Laps and per-second streams | only inside the FIT file | ❌ |
Race position, category, field | ❌ | ✅ |
Critical-power curve | ❌ | ✅ (races only) |
Training load, CTL/ATL/TSB | ❌ | ❌ |
So the downloader lists activities from Zwift, calls the detail endpoint for the summary fields the list omits, downloads and parses each FIT for laps and streams, pulls race results from ZwiftPower, and computes training load locally. Results from the two sites are linked by start time, since they share no identifier — on real data that matches within about three minutes, the time you spend in the pen before the flag drops.
Setup
python3 -m venv .venv && .venv/bin/pip install -r requirements.txt
cp .env.example .env # fill in ZWIFT_USER / ZWIFT_PASSGenerate a bearer token for the server:
python3 -c "import secrets; print(secrets.token_urlsafe(32))"Put it in .env as ZWIFT_MCP_AUTH_TOKEN.
Before the first sync, confirm the endpoints still look the way this code expects — none of them are documented or stable:
.venv/bin/python probe_zwift_api.pyIt writes probe_zwift.json (gitignored) with the raw payloads and prints a
summary. If a section reports an error, fix the mapping before syncing
rather than filling the database with NULLs.
Syncing
.venv/bin/python zwift_downloader.py # incremental
.venv/bin/python zwift_downloader.py --days 30
.venv/bin/python zwift_downloader.py --since 2024-01-01
.venv/bin/python zwift_downloader.py --full # re-fetch everything
.venv/bin/python zwift_downloader.py --with-samples # + per-second streams
.venv/bin/python zwift_downloader.py --backfill-detail
.venv/bin/python zwift_downloader.py --redo-detail # re-parse cached FIT files
.venv/bin/python zwift_downloader.py --skip-fit # no FIT pass (fast)
.venv/bin/python zwift_downloader.py --zp-only # ZwiftPower only
.venv/bin/python zwift_downloader.py --skip-zp # game API only
.venv/bin/python zwift_downloader.py --with-zp-fields # + full race fields
.venv/bin/python zwift_downloader.py --summary # print stats, sync nothingA nightly cron entry:
30 4 * * * cd /opt/zwift-mcp && .venv/bin/python zwift_downloader.py >> sync.log 2>&1The first run is the slow one: it downloads a FIT file per activity. Later runs only fetch what is new, and cached FITs are never re-downloaded.
Running the server
.venv/bin/python mcp_server.py # HTTP (default), port 8081
.venv/bin/python mcp_server.py --transport stdio # local Claude DesktopIn HTTP mode:
/mcp and /mcp/ MCP streamable HTTP endpoint (both spellings work)
/api/v1/... REST API, same bearer token
/api/v1/health liveness probe, unauthenticatedConnect an MCP client with the URL and Authorization: Bearer <token>.
Production
deploy/zwift-mcp.service is a hardened systemd unit for an install under
/opt/zwift-mcp. Running it from a home directory instead means dropping
ProtectHome — it would hide the service's own working directory — and
pointing ReadWritePaths at the install path.
sudo cp deploy/zwift-mcp.service /etc/systemd/system/
sudo systemctl enable --now zwift-mcp
journalctl -u zwift-mcp -fPick a port that nothing else is using (ss -tlnp) and set it in .env;
one MCP server per port.
A nightly sync, staggered against whatever else runs on the box:
15 9 * * * cd /opt/zwift-mcp && .venv/bin/python zwift_downloader.py --days 10 > download.log 2>&1To update a running deployment:
cd /opt/zwift-mcp && ./deploy/update.shThat pulls, installs any new dependencies, restarts the unit and checks the health endpoint — and refuses to run if tracked files have local edits.
.env, the database and fits/ are gitignored, so a pull never touches
them. If the pull changes schema/schema_zwift.sql, note that there are no
migrations — delete the database and re-sync (cached FITs make it cheap).
The database is in WAL mode so the nightly sync and the running server do not block each other. Keep it that way: under the default rollback journal, a long recompute hands live queries "database is locked".
MCP surface
Resources — zwift://athlete, zwift://activities,
zwift://activities/recent, zwift://stats/summary, zwift://stats/monthly,
zwift://training/daily, zwift://power/curve, zwift://racing/results
Read tools
Tool | What it does |
| Filter by sport, world, date, distance, duration, power, races |
| Summary, laps, time in zone, that ride's curve, race result |
| Daily TSS with CTL / ATL / TSB |
| Weekly or monthly volume |
| Thresholds and the power/HR zones derived from them |
| Totals overall, by sport and by world |
| Best mean power per duration, local vs ZwiftPower |
| ZwiftPower results with category and position |
| One race, plus the finishing field if synced |
| Zwift profile, ZwiftPower profile, current form |
| Read-only SELECT against the whole database |
Write tools — rename_activity (pushes to Zwift, then updates locally),
set_local_annotation (local tags and notes, never sent anywhere), and
get_activity_fit_file (where the original FIT lives).
REST API
GET /api/v1/health unauthenticated
GET /api/v1/athlete
GET /api/v1/activities?sport=&world_id=&start_date=&races_only=&limit=
GET /api/v1/activities/{id}?include_samples=
PATCH /api/v1/activities/{id} {"name": …, "local_notes": …}
GET /api/v1/activities/{id}/laps
GET /api/v1/activities/{id}/samples?limit=&offset=
GET /api/v1/stats/summary
GET /api/v1/stats/monthly
GET /api/v1/daily-metrics?start_date=&end_date=&limit=
GET /api/v1/power-curve?source=local|zwiftpower|both
GET /api/v1/races?start_date=&title_contains=&limit=
GET /api/v1/races/{event_id}
GET /api/v1/zwiftpower/profile
GET /api/v1/sync-statecurl -H "Authorization: Bearer $ZWIFT_MCP_AUTH_TOKEN" \
"http://localhost:8081/api/v1/activities?races_only=true&limit=5"Database
athletes — profile, FTP, weight, lifetime totals
worlds — world id lookup (seeded)
activities — one row per ride or run
activity_laps — from the FIT lap messages
activity_samples — per-second stream (only with --with-samples)
activity_zone_distribution — time in zone, computed from samples + FTP
power_curve — best mean power per duration, per activity
segment_results — segment efforts from the Zwift API
zp_profile — ZwiftPower category, zFTP, racing score
zp_results — one row per race
zp_event_results — full finishing fields (--with-zp-fields)
zp_critical_power — ZwiftPower's own CP curve
daily_metrics — derived TSS, CTL, ATL, TSB per day
sync_state — per-dataset watermarks
Views:
activity_summary — km, km/h, w/kg, TSS
monthly_stats — by month and sport
weekly_load — weekly volume and TSS
power_curve_best — all-time best per duration, with the ride that set it
race_results — ZwiftPower results joined to the local activityAll stored values are SI: metres, seconds, watts, bpm, m/s. Conversions live in the views.
Things worth knowing
Training load is computed here, not fetched. Each ride is scaled against the FTP Zwift held at the time (
profileFtp), falling back to the current one.ZWIFT_FTP_OVERRIDEreplaces a stale value.tss_sourcetells you how a TSS was reached —npfrom a parsed FIT, oravg_powerestimated from the summary. The estimate understates a ride with big surges, so it is labelled rather than hidden.Runs are scored against the bike FTP unless
ZWIFT_RUN_FTPis set. Zwift's running power is not the same quantity, so treat those TSS values as indicative.The FIT file is the detail. Without it there are no laps, no streams, no normalised power and no power curve.
Runs recorded without a power meter get no power curve or power zones. Their FIT carries an all-zero power channel, which is absence, not data.
ZwiftPower's critical-power curve covers races only, and only recent ones — an empty curve is a normal answer, not a failure.
The database has no migrations. If a schema column changes, delete
zwift_activities.dband re-sync; cached FITs infits/mean nothing is re-downloaded.ZwiftPower is a separate account link. If the API returns nothing, open zwiftpower.com in a browser once and sign in with Zwift; the profile has to exist there before anything is queryable.
A ZwiftPower failure never fails the sync. Race data is secondary to the game data, so an outage is logged in
sync_stateand skipped.Neither API is public. Field names and endpoints change without notice.
probe_zwift_api.pyexists to tell you which one broke.
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