Show HN: Claude Context but local – semantic code search without API keys

The original requires OpenAI API keys for embeddings and Zilliz Cloud for vector storage. This version runs entirely on your machine using EmbeddingGemma and FAISS.

Key differences: - No API keys needed (uses local EmbeddingGemma model) - Your code never leaves your machine - Zero ongoing costs - Same semantic search quality

Technical details: - Tree-sitter for AST parsing to understand code structure - EmbeddingGemma (1.2GB) for semantic embeddings - FAISS for fast vector similarity search - MCP protocol for integration with Claude Code and other AI tools

Early benchmarks show ~70% reduction in token usage for Claude Code when searching large codebases.

Supports most major languages through Tree-sitter parsers - Python, JS/TS, Go, Java, JSX/TSX, Svelte, with more coming.

GitHub: https://github.com/FarhanAliRaza/claude-context-local

Would love feedback, especially on the approach to code chunking and embedding strategy!