Anatome
by anatome.dev in Developer tools
Log workouts and meals by telling your AI. 873 exercises, muscle diagrams, food lookup.
https://anatome.dev/mcp- Tools
- 36
- open to any client
- Uptime
- 100%
- last 30 days
- Response time
- 351 ms
- 508 ms slowest 5%
- Last check
- Passed
- 8 h ago, next any minute now
Reliability
How to connect
Add it to any MCP client that supports remote servers.
{
"mcpServers": {
"anatome": {
"type": "http",
"url": "https://anatome.dev/mcp"
}
}
}36 tools
- search_exercises
Search 873 exercises by name with muscle/equipment/level filters. Rows are lean (name, ext_id, equipment, level, muscles) — enough to pick one; get_exercise returns instructions and media. Paginates: pass next_cursor back as `cursor`.
- get_exercise
Fetch one exercise by name, id, or random.
- resolve_exercise
Resolve an exercise name into primary/secondary muscle layers for rendering.
- list_muscles
List all 23 supported muscle slugs with anatomical names.
- generate_muscle_image
Render an SVG diagram of the human body with muscles highlighted in arbitrary colors. Returns SVG.
- list_routines
Browse the curated workout routine library (PPL, upper/lower, full-body, 5x5, etc.). Filter by difficulty, goal, split_type, days_per_week. Returns minimal list.
- get_routine
Fetch a single curated routine by slug with all days + slots fully expanded (exercises, sets, reps ranges, rest, superset groupings). The 'give me a full program' tool.
- instantiate_routine
Schedule the signed-in user's routine into planned workouts from start_date. Coach assignment of another user is REST-only.
- search_foods
Search food products by name (Open Food Facts + USDA). Returns macros per 100g.
- lookup_barcode
Lookup a food product by EAN/UPC barcode.
- log_workout
Log a workout with exercise sets (strength or cardio unified). Requires an app user context.
- get_workouts
List the current app user's workouts (most recent first).
- log_meal
Log a meal (calories + macros + optional ingredients) for the current app user.
- get_meals
List the current app user's meals for a date range.
- log_water
Log water intake (ml) for the current app user.
- log_body_metric
Log a body measurement. metric_type: weight (kg), height (cm), body_fat (%), muscle_mass (kg), waist/chest/bicep/forearm/hip/thigh/calf/neck/shoulder (cm), bmi, resting_hr (bpm). Logging weight enables bodyweight-inclusive volume analytics.
- get_body_metrics
List the current app user's body metrics / measurements (weight, height, bicep, body fat, etc.), most recent first. Filter by metric_type (e.g. 'weight', 'bicep') and/or a date range. Requires an app user context.
- upsert_profile
Upsert the current app user's fitness profile. Set `timezone` first: every daily total, streak and adherence window is bucketed by it and defaults to UTC. `weight` doubles as the fallback bodyweight for bodyweight-inclusive volume when no dated weight metric exists.
- get_profile
Get the current app user's fitness profile (height, weight, macro + water goals, diet, active sports). Requires an app user context.
- log_cardio
Log a cardio activity (run/bike/swim/etc.) for the current app user. Supports duration, distance, HR, power, calories.
- get_cardio_activities
List the current app user's cardio activities (most recent first).
- ai_parse_meal
Parse free-text meal description ('2 eggs and toast with butter') into structured items with grams + macros.
- ai_photo_macros
Analyze a meal image and estimate foods + macros. Pass exactly one of image_url or image_base64. Vision model, capped separately from the text AI budget (free tier 1/mo).
- ai_meal_plan
Draft a meal plan. Not medical advice. confirm:true required. Pass health constraints so the draft can honour them.
- ai_workout_plan
Draft a workout plan. Not medical advice. confirm:true required. Pass health constraints so the draft can honour them.
- get_muscle_recovery
Per-muscle 7-day recovery % (Fitbod parity) — the 'what should I train today?' input. Recommends fresh muscles. Pass include_bodyweight=true to add the user's bodyweight to bodyweight exercises so recovery reflects real load.
- get_nutrition_daily
Per-day calories, macros, fiber/sugar/sodium/alcohol, water, targets and adherence % over a date range (default: last 7 days). The 'how am I tracking today?' tool. Requires X-App-User-Id.
- get_water
List the current app user's water intake entries for a date range. Requires X-App-User-Id.
- update_meal
Correct a previously logged meal — name, macros, nutrients, portion, date or meal_type. Pass only the fields you want to change. Requires X-App-User-Id.
- delete_meal
Delete a logged meal by id (soft delete, 30-day recovery window). Requires X-App-User-Id.
- update_sets
Correct sets already logged, by set id (log_workout returns them). Relabel the exercise, fix weight/reps/rpe, mark completed, add notes, or delete. Selection and change are separate, so a subset can be relabelled. Adding a set is log_workout, not this.
- delete_workout
Delete a logged workout and its sets by id (soft delete, 30-day recovery window).
- export_data
Export the signed-in user's data as JSON. Pass `domains` (e.g. meals,workouts) or confirm:true for a full copy. Identity comes from the token, never a caller-supplied user id.
- get_events
What changed since a cursor, including DELETES, which a list read cannot show. Returns {seq, entity, id, action}. Pass the last seq back as `since` on the next call to receive only entries after it; omit `since` for a first sync. seq is a global counter: gaps in your feed are…
- my_training_context
Returns a slice of the signed-in user's training picture. Default domains are workouts and today's nutrition. Pass `domains` to add checkin, notes or profile, or `domains=all`. Identity comes from the token, not a caller-supplied user id.
- get_progress
Any progression metric for the current user — pick one in `metric`. training_load is acute:chronic (>1.5 ramping too fast, <0.8 detraining); muscle_recovery is per-muscle freshness; correlate takes metric_a vs metric_b. Only completed sets count.
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Recent checks
| When | Result | HTTP | Time |
|---|---|---|---|
| 8 h ago | Passed | 200 | 564 ms |
| 18 h ago | Passed | 200 | 508 ms |
| 27 h ago | Passed | 200 | 358 ms |
| 37 h ago | Passed | 200 | 300 ms |
| 47 h ago | Passed | 200 | 335 ms |
Show 4 older checks
| 2 days ago | Passed | 200 | 232 ms |
| 3 days ago | Passed | 200 | 356 ms |
| 3 days ago | Passed | 200 | 351 ms |
| 4 days ago | Passed | 200 | 306 ms |