@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.
๐ Official Documentation & Website: putervision.com
โก 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
๐ Key Highlights
- ๐ Deterministic 3D/2D Spatial Memory & Compact Slices: Zero LLM in the loop for spatial indexing; deterministic SQLite WAL queries with FTS5 search, 3D Euclidean proximity radius lookups, and sub-1KB observer-relative compact slices ($K \le 16$ nearest entities) for System 1 fast path evaluation.
- โก 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.
- โณ 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 โ hidden โ lost).
- ๐ Collision & Movement Simulation: Predicts entity displacement trajectories, detects AABB obstacle collisions, and computes obstacle-avoiding navigation waypoints before actions execute.
- ๐ฎ Playwright Game Automation: Generates timed WASD / Arrow keyboard hold sequences (
KeyW for 450ms, ArrowLeft for 290ms) and 3Dโ2D coordinate screen projections.
- ๐ค Multi-Agent Spatial Blackboard: Topic-based coordination with TTL, mutex locks, and collision intent alerts across parallel subagents.
- ๐ก๏ธ Spatial Spec-Driven Development (Spatial SDD): Physical design contract baseline registration, live verification (clearance, bounds, containment), and cryptographic SHA-256 evidence bundles.
- ๐จ Interactive 3D WebGL Visualizer: Browser-based Three.js 3D viewport rendering active entities, orientation axes, frustum cones, and topological links (
world-model-mcp view).
- ๐ 100% Local & Private: All spatial entities, relations, and history stay inside
.world-model-mcp/ in your workspace.
๐ ๏ธ 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, and format: "compact_slice").
- 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, 3Dโ2D screen ray projection).
๐ For complete parameter specifications, return schemas, and example payloads, see the API Reference Guide and Database Schema.
๐ Architecture & Spatial Memory Lifecycle
Perception / Vision Detection
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โ Perception Ingestion & Re-ID โ โโโถ ingest_observation(reconcile: true)
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โ Durable Entity & Permanence โ โโโถ update_entity(...)
โ (3D Bounding Boxes, Decay) โ โโโถ set_relation(relation: "on"|"inside")
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โ Simulation & Waypoint Routing โ โโโถ simulate_movement(mode: "navigate")
โ (AABB Collision Avoidance) โ โโโถ get_expected_view(fov: 90)
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โ Playwright & Action Execution โ โโโถ generate_game_inputs(...)
โ (WASD Sequences, Screen Rays) โ โโโถ record_outcome(action_type: "move")
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โ Spatial SDD & Cryptographic โ โโโถ manage_spatial_spec(action: "verify")
โ Evidence Bundling to Tasks โ โโโถ create_evidence_pack(...)
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โ Persistent SQLite Engine โ โโโถ .world-model-mcp/world.db (WAL mode)
โ Append-Only History Ledger โ โโโถ SHA-256 Cryptographic Audit Chain
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๐ Documentation Directory
Explore dedicated guides and deep dives in the docs/ directory: