Servidor MCP de Anatome

• Nombre en el registrodev.anatome/anatomeverificado en el registro MCP

El nombre en el registro está bajo anatome.dev. El registro solo permite usar ese espacio de nombres a quien demuestra control del dominio por DNS o HTTP.

• Estadorespondecomprobado el 2026-10-21
• Herramientas36
• El servidor se llamaanatome
• Versión del servidor2.7.1
• Versión del protocolo2025-06-18

El 2026-10-21 el servidor respondió a initialize y tools/list sin iniciar sesión. Primera respuesta en 807 ms.

• Aún no se ha juzgado si sus herramientas hacen el trabajo del producto.
• Comprobado 2 de los 7 días necesarios para juzgar su fiabilidad.

Lo dicen reglas a partir de las mediciones de arriba. La primera llamada probable la elige un modelo de la lista de herramientas; lee su descripción antes de fiarte.

• Nota INITE MCPtras una semanala nota necesita 7 comprobaciones diarias: 2 hasta ahora
• Respondiómidiendo2 de las 7 comprobaciones diarias necesarias para mostrar el porcentaje
• Mediana de la primera respuesta916 ms
• Espacio en el contexto del agente≈ 4201 tokenslas definiciones de todas sus herramientas (36), que el agente lleva en cada turno
• Definiciones de herramientasB · 86 de 100
• Resultados tipados20 de 36 herramientasdeclaran outputSchema: el resultado llega tipado y se lee de una vez

• Parámetros sin descripción: en 30 de 36

Un programa comprueba el servidor una vez al día: initialize y tools/list, sin modelo. Los tokens son la longitud de las definiciones, a unos cuatro caracteres por token. La nota promedia seis comprobaciones del nombre, la descripción, el esquema y las anotaciones de cada herramienta; dice lo bien descritas que están, no si funcionan. La nota pondera solo lo medido: si responde (30%), si hace el trabajo del producto (25%), definiciones (20%), contexto (10%) y uso (15%). Lo que no se midió queda fuera, y una instrucción oculta limita la nota a 40. El estado de los servidores MCP de los proveedores: método y números →

• 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…

• 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…

• 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…

• 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…