restaurant-ksor

restaurant-ksor is a demo Knowledge System of Record (KSoR) for a restaurant, built with @panaversity/ksor. It holds governed, versioned, human-approved documents — menu, dietary/allergen info, reservation policy, refund policy, and hours — published as both a browsable website for people and a citable MCP server for AI agents.

Documents

This record contains 7 documents:

1. welcome.md — Introduction and navigation

2. menu.md — Full menu with prices and ingredients

3. allergens-and-dietary.md — Allergen and dietary information for every dish

4. policies/reservations.md — Reservation policy and deposit terms

5. policies/refunds-and-cancellations.md — Refund and cancellation terms

6. hours-and-location.md — Operating hours and location

7. faq.md — Frequently asked questions

Related MCP server: mcp-rag-bridge

Setup

npm install           # Install dependencies (once)
npm run dev           # Start the dev site at http://localhost:3000

# For the MCP server (requires Postgres + embedding provider key):
npm run provision     # Apply schema and grants (once)
npm run refresh       # Build, ingest, and activate the latest generation
npm run serve         # Start the MCP server at http://127.0.0.1:8080/mcp

See AGENTS.md for full setup instructions including database configuration.

Known Limitations

Abstention floor: not calibrated. This 7-document, single-restaurant corpus does not separate cleanly between in-corpus and out-of-corpus questions by embedding similarity — near-miss questions (e.g. "do you have a kids' menu?") scored 0.58–0.62, overlapping our weakest in-corpus scores (~0.57–0.59). Attempted twice with hand-written query files, not just generic auto-generated ones. Scope enforcement therefore relies on the connected agent reading this document's declared scope and exclusions, not a measured vector floor.

License

This project was scaffolded with ksor init version 0.0.60.