@putervision/world-model-mcp
v0.4.1
Published
Deterministic, persistent 3D/2D spatial world model for AI agents with entity tracking, object permanence, movement simulation, and expected view frustum projection.
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@putervision/world-model-mcp
@putervision/world-model-mcp is a zero-infrastructure, deterministic Model Context Protocol (MCP) server that maintains a persistent 3D/2D spatial world model for AI agents. It bridges perception (@putervision/vision-memory-mcp) and reasoning/action (@putervision/state-memory-mcp) with durable entity tracking, object permanence with confidence decay, movement simulation with AABB collision avoidance, expected view frustum projection, and Playwright 3D game automation.
🌐 Official Documentation & Website: putervision.com
⚡ Quick Start & Installation
Prerequisites: Node.js >= 18.18.0
# 1. Install globally
npm install -g @putervision/world-model-mcp
# 2. Navigate to your project directory
cd your-project
# 3. Initialize world-model-mcp
# Creates .world-model-mcp/, updates .gitignore, registers project,
# and scaffolds IDE instructions and MCP configs for Cursor, Claude, VS Code, Windsurf, etc.
world-model-mcp init
# Done! Restart your IDE or Agent Manager to activate.Alternative Options
# Run directly via binary (after global install)
world-model-mcp run
# Launch interactive 3D WebGL Scene Visualizer
world-model-mcp view
# Display database metrics and permanence confidence stats
world-model-mcp stats🌟 Key Highlights
- 🌐 Deterministic 3D/2D Spatial Memory: Zero LLM in the loop for spatial indexing; deterministic SQLite WAL queries with FTS5 search and 3D Euclidean proximity radius lookups.
- ⚡ 15 Production-Grade Consolidated MCP Tools: Full CRUD, topological spatial graphs (
on,inside,contains,near), ray-AABB occlusion frustum culling, waypoint navigation, and time-travel rollback. - ⏳ Object Permanence & Decay: Entities remain in persistent memory even when out of view, with configurable exponential confidence decay ($C = C_0 \cdot e^{-\lambda t}$) and status lifecycles (
active→hidden→lost). - 🚀 Collision & Movement Simulation: Predicts entity displacement trajectories, detects AABB obstacle collisions, and computes obstacle-avoiding navigation waypoints before actions execute.
- 🎮 Playwright Game Automation: Generates timed WASD / Arrow keyboard hold sequences (
KeyW for 450ms,ArrowLeft for 290ms) and 3D↔2D coordinate screen projections. - 🤝 Multi-Agent Spatial Blackboard: Topic-based coordination with TTL, mutex locks, and collision intent alerts across parallel subagents.
- 🛡️ Spatial Spec-Driven Development (Spatial SDD): Physical design contract baseline registration, live verification (clearance, bounds, containment), and cryptographic SHA-256 evidence bundles.
- 🎨 Interactive 3D WebGL Visualizer: Browser-based Three.js 3D viewport rendering active entities, orientation axes, frustum cones, and topological links (
world-model-mcp view). - 🔒 100% Local & Private: All spatial entities, relations, and history stay inside
.world-model-mcp/in your workspace.
🛠️ MCP Tool Suite
@putervision/world-model-mcp provides 15 production-grade consolidated MCP tools organized across 5 core workflow domains:
- Spatial Memory & Search:
update_entity(entity CRUD, 3D bounds, properties, confidence),query_entities(FTS5 search, proximity radius, status/tags filter, history lookup),set_relation(topological graph links:on,inside,near,contains),get_spatial_map(JSON, GeoJSON, glTF 2.0, OBJ, summary). - Simulation & Vision Integration:
simulate_movement(displacement prediction, AABB collision checks, waypoint routing),ingest_observation(vision detection ingestion, Euclidean re-identification, frustum reconciliation),get_expected_view(observer pose, horizontal FOV cone, ray-AABB occlusion). - Goal & State Integration:
link_to_goal(associate entities/regions with State Memory tasks, extract spatial context slices),record_outcome(record execution results, position shifts, property changes, destruction). - Spatial SDD & Proofs:
manage_spatial_spec(register physical clearance/containment contracts, live verification scoring),create_evidence_pack(cryptographic SHA-256 evidence bundles linking spatial proofs to task nodes). - Multi-Agent, Replay & Automation:
use_spatial_blackboard(topic board, mutex claim/release, intent conflicts),manage_snapshot(checkpoints, snapshot diffing, time-travel undo),wait_for_spatial_state(async polling for target spatial condition),generate_game_inputs(Playwright WASD hold timings, 3D↔2D screen ray projection).
👉 For complete parameter specifications, return schemas, and example payloads, see the API Reference Guide and Database Schema.
🚀 Architecture & Spatial Memory Lifecycle
Perception / Vision Detection
│
▼
┌─────────────────────────────────┐
│ Perception Ingestion & Re-ID │ ──▶ ingest_observation(reconcile: true)
└────────────────┬────────────────┘
│
▼
┌─────────────────────────────────┐
│ Durable Entity & Permanence │ ──▶ update_entity(...)
│ (3D Bounding Boxes, Decay) │ ──▶ set_relation(relation: "on"|"inside")
└────────────────┬────────────────┘
│
▼
┌─────────────────────────────────┐
│ Simulation & Waypoint Routing │ ──▶ simulate_movement(mode: "navigate")
│ (AABB Collision Avoidance) │ ──▶ get_expected_view(fov: 90)
└────────────────┬────────────────┘
│
▼
┌─────────────────────────────────┐
│ Playwright & Action Execution │ ──▶ generate_game_inputs(...)
│ (WASD Sequences, Screen Rays) │ ──▶ record_outcome(action_type: "move")
└────────────────┬────────────────┘
│
▼
┌─────────────────────────────────┐
│ Spatial SDD & Cryptographic │ ──▶ manage_spatial_spec(action: "verify")
│ Evidence Bundling to Tasks │ ──▶ create_evidence_pack(...)
└────────────────┬────────────────┘
│
▼
┌─────────────────────────────────┐
│ Persistent SQLite Engine │ ──▶ .world-model-mcp/world.db (WAL mode)
│ Append-Only History Ledger │ ──▶ SHA-256 Cryptographic Audit Chain
└─────────────────────────────────┘📚 Documentation Directory
Explore dedicated guides and deep dives in the docs/ directory:
| Guide | Description |
| :--- | :--- |
| 🏗️ Architecture & Codebase Distillation | High-signal architectural overview, module inventory, data flows, and design decisions. |
| 💡 Features & Triad Overview | PuterVision Autonomous Triad interaction, 3D WebGL scene visualizer, and evidence packs. |
| 📋 Spatial World Model Concepts | Object Permanence ($C = C_0 \cdot e^{-\lambda t}$), Confidence Decay, Frustum Projection, and Spatial SDD. |
| ⚙️ Configuration & IDE Setup | Auto-Initialization details, Environment Variables, and Editor Configs (Cursor, VS Code, Claude, Windsurf). |
| 🛠️ CLI Command Reference | CLI flags (init, run, view, stats, inspect, map, export, import, doctor, snapshot, spec, blackboard). |
| 🧰 Tools & API Reference | Complete reference for all 15 Consolidated MCP Tools, legacy tool mapping, and parameter examples. |
| 🗄️ Database Schema | SQLite tables (entities, spatial_relations, entity_history, spatial_specs, blackboard_items, evidence_packs). |
| 🎮 Interactive 3D Game Arena Demo | Autonomous 3D browser arena with Three.js bridge diagnostics (window.__WORLD_MODEL_BRIDGE). |
| 🧭 Examples & Tutorials | Deep-dive examples: Spatial Navigation, Perception Reconciliation, and Multi-Agent Blackboard. |
📖 Agent Playbook: 5-Step Canonical Workflow
When an autonomous AI agent enters a repository with world-model-mcp:
1. Orient & Explore ──▶ get_spatial_map(format: "summary") + get_expected_view(fov: 90)
2. Query & Locate ──▶ query_entities(query: "chest", radius: 15) + query_entities(entity_id: "...")
3. Plan & Simulate ──▶ simulate_movement(mode: "navigate") + manage_spatial_spec(action: "verify")
4. Execute & Ingest ──▶ generate_game_inputs(...) + ingest_observation(reconcile: true)
5. Record & Evidence ──▶ record_outcome(...) + create_evidence_pack(task_id: "...")🧪 Testing
# Run full unit, integration, and geometry stress test suite across 47 test files (206 tests)
npm test
# Run multi-Node matrix test suite across Node.js 18, 20, and 22
npm run test:matrix
# Run 3D geometry, projection, and Playwright game loop tests
npm run test:3d⚖️ License & Disclaimers
Developed and maintained by PuterVision. Released under the MIT License.
- Local Storage Guarantee: All spatial coordinates, bounding volumes, and entity history remain 100% local in your workspace. No telemetry or project data is ever transmitted.
- Trademarks & Non-Affiliation: Product names (Cursor, Claude Code, Gemini, Windsurf, VS Code, GitHub, SQLite, Three.js, Playwright) are property of their respective owners and used solely for compatibility identification.
