# Anatome Muse connector

From musedirectory.ai, the independent directory of Meta Muse connectors. Not affiliated with Meta.

## Anatome

Log workouts and meals by voice. Access 873 exercises, muscle diagrams, and food nutrition data.

- Record: https://musedirectory.ai/connector/anatome
- Category: Health
- Developer: dev.anatome (https://anatome.dev)
- Muse status: Extra setup. Not in Muse's Connectors list yet. Muse can still use it: its page gives you a request to paste into Muse.
- Health: Working, 193ms, checked 2026-09-28T07:45:54Z
- Endpoint: https://anatome.dev/mcp
- Auth: No account needed; Pricing: unknown
- Screening: Screened, no issues found (2026-09-24T22:25:52Z)
- Source: Found in the official MCP Registry (dev.anatome/anatome) https://registry.modelcontextprotocol.io/v0/servers?search=dev.anatome%2Fanatome

Connects to a fitness tracking platform with 873 exercises, muscle anatomy diagrams, and food database. Muse can log workouts, meals, body metrics, and water intake; generate personalized workout and meal plans; and track recovery and progress over time.

Example request: "Log my workout today: three sets of ten bench press at 185 pounds, then a five-mile run."

How to connect: Not in Muse's Connectors list yet, but Muse can still use it. Paste this into Muse: "Use Anatome to help me. It is a free service with an MCP server at https://anatome.dev/mcp. It does not need an API key. Ask me before you share anything with it." Muse asks before it shares anything with the app's site. Meta does not review apps used this way, so only use ones you trust. We tested this in the Muse app on September 24, 2026: Muse used an app's link directly this way and returned a live answer.

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 oth
- 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.

Screening checks:
- MCP handshake: pass (Answered in 839ms)
- Domain against threat feeds (Cloudflare security DNS): pass (anatome.dev not flagged)
- Published packages against the OSV malicious-package database: n/a (No npm or PyPI package published)
- Hidden instructions or invisible characters in tool text: pass (36 tools read, nothing found)
- Inputs asking for passwords, card numbers or seed phrases: pass (None found)
- Domain and redirects: pass (Domain registered 114 days ago)
- AI review of purpose and tool behavior: pass (No concerns)