Anatomy Engine

A 3D full-body anatomy + biomechanics engine, exposed as a Model Context Protocol (MCP) server with an inline 3D viewer. It gives an AI agent (or any app) real anatomical structure, biomechanical relationships, and an interactive body to render.

⚠️ Awaiting clinician approval. The anatomical & clinical data is AI-authored and has not yet been reviewed by a licensed clinician. For educational purposes only — educational & directional, not diagnostic. See disclaimer.

<p align="center"> <img src="docs/screenshots/nervous.png" width="49%" alt="Nervous system — brain, spinal cord and peripheral nerves" /> <img src="docs/screenshots/cardiovascular.png" width="49%" alt="Cardiovascular system — heart and vascular tree" /> </p> <p align="center"><em>Skeleton + muscles (top) · nervous system · cardiovascular system — any of 7 systems, toggled independently.</em></p>

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What it is

• 22 MCP tools over a hand-authored knowledge core — structures, connections, innervation, blood supply, fascial chains, muscle roles, movements, postures, task activation, and correctives.
• 7 real Z-Anatomy systems (skeletal, muscular, nervous, cardiovascular, visceral, ligamentous, skin), Draco-compressed, with a mobile "lite" tier.
• A bone-identity rig — hover to identify any part, click for its biomechanical links, isolate a region, and articulate named postures (pelvic tilt, forward head, rounded shoulders…).

It's the reusable core beneath LooksLab; it has no accounts or paywall of its own.

Quick start

npm install
npm run playground   # → http://localhost:4599  (every tool as a button + live 3D viewer)
npm test             # smoke tests
npm run validate-data

Use as an MCP server

Once published, point any MCP client at the package:

{
  "mcpServers": {
    "anatomy-engine": { "command": "npx", "args": ["-y", "@ajfutures/anatomy-engine"] }
  }
}

Or run straight from a local checkout — { "command": "npx", "args": ["tsx", "src/index.ts"], "cwd": "…/anatomy-engine" }.

The 22 tools

All reads are educational & directional, not diagnostic. Every tool returns structured JSON.

Browse & search

Tool	Params	What it returns
list_systems	—	The 7 anatomical systems, in load-priority order.
list_structures	system?	All structures, optionally filtered to one system.
get_structure	id	One structure: English/Latin names, region, side, description, and the patterns it participates in.
search_anatomy	query	Fuzzy natural-language → structure ids (handles gym slang: "glute", "hammy", "rear delt"). Structured outputSchema. Resolve a plain name to an id before calling other tools.
focus_region	region, side?	Every structure in a body area (optionally one side) + a viewer URL that isolates it.

Connections & biomechanics

Tool	Params	What it returns
get_relationships	id	Curated biomechanical links (antagonist / synergist / coupled) with functional notes + corrective ideas.
get_connections	id	Everything connected to a structure — typed (regional / synergist / antagonist / kinetic_chain / fascial / attachment), grouped + flat.
get_fascial_chain	id | chain	Myofascial (Anatomy-Trains) lines a structure sits in, or a line's members — to trace tension up/down the chain.
get_muscle_roles	id, action	For a movement (e.g. "hip extension"), classifies the structure's role and lists agonists / antagonists / synergists / stabilizers.
describe_movement	joint, direction	Range of motion, which muscles shorten vs. lengthen, and the downstream postural effect.
get_pose	name	A named posture (e.g. anterior_pelvic_tilt) as joint-angle targets + its tight/weak muscle-balance read.
analyze_task	task, phase?	Muscle activation by phase for a multi-joint task (gait, squat, hip_hinge, overhead_press).
list_patterns	—	The named postural muscle-balance patterns (crossed syndromes, pronation chain).
get_pattern	id	A pattern's likely-tight and likely-weak muscles, what it's measured by, and full corrective detail.
get_interventions	id, goal	Corrective options for a structure by goal (release / stretch / strengthen / mobilize).

Anatomy facts

Tool	Params	What it returns
get_innervation	id	Nerve supply: nerve, spinal roots (myotome), plexus.
get_blood_supply	id	Arterial supply + venous/lymphatic drainage.

Clinical — educational & red-flag-screened, never diagnostic

Tool	Params	What it returns
get_referred_pain	id	Trigger-point referral zones a muscle commonly sends sensation to (e.g. upper trapezius → temple).
list_pathologies	id	Conditions associated with a structure, each with common signs + red flags to screen for.
get_contraindications	target	Movements/loads to be cautious with — by pathology id, or a structure id (aggregates its conditions).
map_symptoms	region, symptom	Structures/conditions in an area to learn about — explicitly not a diagnosis, not ranked, always returns red flags and points to in-person care.

Viewer

Tool	Params	What it returns
show_anatomy	systems?, pose?, region?	The resolved selection + the ui://anatomy/viewer inline 3D resource (hover-identify, click, isolate, articulate).

Using it with an AI agent

The point of the engine is that an agent can chain these tools to reason about a real question — turning a vague, plain-language ask into structured anatomy, then a grounded, sourced answer. Five examples:

1. "What exercises are beneficial for anterior pelvic tilt?" The agent calls get_pose("anterior_pelvic_tilt") → get_pattern("lower_crossed_syndrome") to read out which muscles are likely tight (hip flexors / iliopsoas, lumbar erectors) and likely weak (glutes, deep core), then get_interventions(...) on each. → "Release and stretch the hip flexors and low back; strengthen the glutes and deep core — here are specific correctives."

2. "My lateral hip aches when I sleep on that side — what could it be and what should I avoid?" map_symptoms("hip", "ache lying on my side") surfaces the gluteus medius and gluteal tendinopathy → list_pathologies("gluteus_medius") for signs + red flags → get_contraindications("gluteal_tendinopathy"). → "This pattern is often gluteal tendinopathy; commonly aggravated by crossing the legs and side-lying — things to be cautious with are X, Y. These red flags mean see a clinician." (Never a diagnosis.)

3. "Which muscles are the prime movers coming up out of a squat?" analyze_task("squat", "ascent"). → "Prime movers: gluteus maximus and quadriceps; synergists: hamstrings, adductor magnus, soleus; stabilizers: lumbar erectors and abdominals."

4. "I keep getting tension headaches and my upper traps are tight — what's the link?" search_anatomy("upper trap") → get_referred_pain("upper_trapezius") (refers to the temple) + get_pattern("upper_crossed_syndrome") → get_interventions(...), with list_pathologies red-flag screening for cervicogenic headache. → "The upper trapezius refers pain to the temple and is a classic driver of tension headaches with forward-head posture; here's how to release it — and these red flags warrant a professional."

5. "Show me forward-head posture in 3D and the muscles involved." get_pose("forward_head") for the tight/weak read, then show_anatomy({ systems: ["skeletal","muscular"], pose: "forward_head" }) returns the inline 3D viewer articulated into that posture, with the involved muscles highlightable. → An interactive body the user can rotate, plus the muscle-balance explanation.

In each case the engine supplies the structured anatomical facts and relationships; the agent does the plain-language conversation and turns them into recommendations — grounded, and consistently framed as educational, not diagnostic.

Disclaimer

This engine is for education and orientation only. It is not medical advice, not a diagnosis, and not a substitute for a licensed clinician. The clinical tools ship with red-flag screening and non-diagnostic framing.

Status: awaiting clinician approval — for educational purposes only. The anatomical/clinical data is AI-authored and has not yet been reviewed by a licensed clinician.

License & attribution

• Code & data: MIT — see LICENSE.
• 3D meshes: derived from Z-Anatomy (CC BY-SA 4.0), itself from BodyParts3D/DBCLS. Attribution + share-alike obligations apply wherever the meshes are displayed — see NOTICE. The meshes are not bundled in the npm package; they're built by pipeline/export.py and served from a hosted asset base.