v0.24.0 is out — SHA-256 incremental re-scan, surprises detection & more

Your codebase,
finally understood

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.

pip install rekipedia → View on GitHub
~/my-project
reki scan .
✔ Scanned 312 files · 4,891 symbols indexed
✔ Wiki generated · .rekipedia/wiki/
Done in 4.2s
reki ask "how does the auth flow work?"
The entry point is src/auth/middleware.py:42
AuthManager.verify() validates the JWT and attaches
the user to the request context.
Sources: src/auth/middleware.py:42, src/models/user.py:18
v0.24.0 highlights

Paste code. Watch the graph mutate.

rekipedia performs deterministic static analysis on your code. Edit the code below to see how relationships and hotspots are parsed instantly.

Python Code Editor
Live Abstract Syntax Tree (AST)
4 nodes · 3 edges · Hub: authenticate()
Symbols Found (Nodes)
AuthService
authenticate
validate_token
create_session
Call Relationships (Edges)
AuthService authenticate (contains)
authenticate validate_token (calls)
authenticate create_session (calls)
Pure client-side static parser running locally on your screen. No code ever leaves your browser.
Deterministic Path Finder

Select two components to trace the shortest call-path in the graph. Demonstrates the shortest_path MCP tool.

Client
AuthService
TokenStore
Database
Active Path: ClientAuthServiceTokenStoreDatabase (Length: 3 hops)

Everything you need to understand any codebase

From a first-time scan to live AI agent integration — rekipedia covers the full workflow.

🔍
reki ask
Grounded Q&A
Ask anything about your codebase and get answers with exact file:line citations. No hallucinations — every answer is sourced from your index.
🌐
reki serve
Local Wiki UI
Spin up a browseable wiki at localhost:7070. Auto-generated architecture docs, module maps, and relationship graphs — all from your actual code.
🔌
reki mcp
MCP Server
Expose your knowledge base as an MCP server. Claude Code, Cursor, and any MCP-compatible agent can query your codebase with structured tools — not just file dumps.
🔥
reki hotspots
Architectural Risk
Find hub nodes (files with 40+ dependents) and bridge nodes (the connective tissue between clusters) before you start a refactor. Know what you're touching.
🚀
reki onboard
Instant Onboarding
Generate a structured architecture walkthrough for new team members in seconds. No more "read the code and figure it out" onboarding.
reki watch
Always Fresh
Auto-reindex on every file save. Your wiki stays in sync as you code — no manual rebuilds, no stale docs.

From repo to knowledge base in three steps
1

Scan your repo

rekipedia parses every file into a modular storage layer — symbols, call graphs, module relationships, and dependency trees, backed by focused storage modules for performance and clarity.

reki scan .
2

Ask anything

Query your codebase in plain English. Every answer comes with exact file:line citations — grounded, verifiable, no guessing.

reki ask "where is rate limiting handled?"
3

Connect your agent

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.

reki mcp
Give your AI agent a real knowledge base

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.

Claude Code Cursor Any MCP Client
askGrounded Q&A with file:line citations
search_nodesFind symbols, functions, and classes by name or pattern
get_contextFull context for any symbol — callers, callees, docstring
get_relationshipsDependency graph between modules and files
get_hub_nodesMost connected files — the load-bearing walls of your repo
get_impactBlast radius analysis — what breaks if you change X?

Get started in seconds
$ 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.

Ollama (default)
Run fully local, zero cost
REKIPEDIA_MODEL=ollama/llama4
OpenAI
GPT-4o, o1, and more
OPENAI_API_KEY=sk-...
Anthropic
Claude 3.5 Sonnet, Opus
REKIPEDIA_MODEL=claude-3-5-sonnet-...
Google Gemini
Gemini 2.0 Flash and Pro
REKIPEDIA_MODEL=gemini/gemini-2.0-flash
OpenRouter
100+ models via one key
REKIPEDIA_MODEL=openrouter/...
Azure OpenAI
Enterprise deployments
REKIPEDIA_MODEL=azure/gpt-4o

Stop copy-pasting code.
Start asking questions.

rekipedia is MIT licensed, language-agnostic, and works anywhere Python runs.

⭐ Star on GitHub View install options