Compress an entire codebase into a single markdown context file.
Feed it to any LLM once instead of re-reading your repo every conversation.
Achieved 96% compression on a 262-file repo (154,229 → 6,487 tokens).
What's included
Static analysis— Tree-sitter AST parsing for Python, JS, TS, Go, Rust;
regex fallback for Java, Ruby, C#, C/C++, Swift, Kotlin, Shell, and moreArchitecture analysis— single LLM call identifies layers, components,
entry points, and data flowSemantic relationships— LLM-discovered producer/consumer links,
shared data structures, parallel implementations, and polyglot bridgesMulti-provider support— OpenAI, Claude, Deepseek, Gemini, Groq, Ollama,
Mistral, xAI, Perplexity, OpenRouterOne-liner installers— no manual venv or config setup required
Install
Mac / Linux:
curl -fsSL https://github.com/KrishivPiduri/repo-brain/releases/latest/download/install.sh | bash
Windows (PowerShell): irm https://github.com/KrishivPiduri/repo-brain/releases/latest/download/install.ps1 | iex
Assets
Upload these files to this release:
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install.sh
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install.ps1
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repo-brain.zip (zip of: main.py, llm.py, ingest.py, analyze.py, relationships.py, generate_prompt.py, mcp_server.py,
config.example.py, requirements.txt)