I shipped four releases of world-model-mcp in twelve days. v0.6.1 to v0.7.2. The pitch is "AI coding agents lose context across compaction, repeat the same mistakes, and hallucinate APIs that do not exist." Before I write more about it I wanted to demonstrate the primitives on a real codebase, with real outputs, not screenshots someone has to take my word for.
The codebase is the project's own repo. I ran python -m world_model_server.cli setup (it auto-seeded 598 entities from the source), then ran scripts/demo_seed.py which inserts the small set of constraints, facts, and a compaction audit row that real PostToolUse / record_correction hook activity would write organically over one to two weeks of development with Claude Code installed.
Every output block below is verbatim from the actual SQLite database after running the actual command. You can reproduce every output here by cloning the repo, running python -m world_model_server.cli setup, then python scripts/demo_seed.py. The script is idempotent and supports --dry-run and --reset.
Install: pip install world-model-mcp. Source: github.com/SaravananJaichandar/world-model-mcp.
1. A learned constraint denying an edit at the PreToolUse boundary
