rekipedia turns any repository into a searchable wiki with grounded Q&A, exact file:line citations, and an MCP server so your AI agent actually knows your code.
From a first-time scan to live AI agent integration — rekipedia covers the full workflow.
file:line citations. No hallucinations — every answer is sourced from your index.localhost:7070. Auto-generated architecture docs, module maps, and relationship graphs — all from your actual code.rekipedia parses every file into a SQLite knowledge store — symbols, call graphs, module relationships, and dependency trees.
Query your codebase in plain English. Every answer comes with exact file:line citations — grounded, verifiable, no guessing.
Start the MCP server and connect Claude Code or Cursor. Your AI agent now queries a real knowledge base — not just whatever you remember to paste in.
Most "AI + codebase" tools work by dumping file contents into context windows. That doesn't scale, doesn't persist, and doesn't let agents reason about structure.
With reki mcp, your agent can ask "If I change engine.py, what else breaks?" and get a real dependency graph back. Drop a .mcp.json in your project and Claude Code or Cursor connects automatically.
$ pip install rekipedia
$ uvx rekipedia init . && uvx rekipedia scan .
$ npx rekipedia init . && npx rekipedia scan .
$ pip install "rekipedia[rag]"
Works with any OpenAI-compatible endpoint. Run local with Ollama or connect to any cloud provider.