Pharaoh - Your AI breaks things it can't see

# Pharaoh — Codebase Intelligence for AI Coding Agents > Pharaoh maps your codebase into a knowledge graph and gives AI coding tools full architectural awareness — every function relationship, dependency chain, module boundary, and entry point — before they write a single line. ## The Problem Pharaoh Solves AI coding tools read your codebase one file at a time. On a 200-file repo, the AI sees fragments — never architecture. The result: - It creates a retry utility without knowing one exists three modules away - It refactors a function without knowing 14 downstream callers depend on the exact signature - It writes new endpoints that are never wired to any entry point - It produces PRDs that ignore existing module boundaries and duplicate existing functionality - It burns 40K+ context tokens reading files to build understanding that a 2K-token graph query provides instantly This isn't an AI limitation. It's a context limitation. The AI is smart enough — it just can't see the codebase. ## How It Works Pharaoh gives AI tools the complete structural picture: 1. **Install the GitHub App** (read-only access, 30 seconds) 2. **Automatic parsing** — tree-sitter extracts every function, import, export, call chain, endpoint, cron handler, and environment variable from TypeScript and Python codebases 3. **Knowledge graph** — all relationships stored in Neo4j with dual-layer per-tenant isolation 4. **MCP endpoint** — your AI tool queries the graph silently before every decision 5. **Always current** — webhooks re-map on every push to your default branch 6. **PR Guard** — automated structural checks on every pull request (reachability, regression risk, test coverage, breaking changes) No config files. No per-repo setup. No maintenance. Source code is read during parsing and immediately discarded — only structural metadata is stored. ## The 16 MCP Tools - [Recon](https://pharaoh.so/llms-full.txt#recon): Batched reconnaissance — codebase map + modu