VectorCode
Semantic code search MCP server using embeddings.
Find code by meaning, not just by name.
curl -fsSL https://raw.githubusercontent.com/alejandro-technology/vectorcode/main/install.sh | bash Requires Rust 1.75+ for manual build
Search Beyond Keywords
Fills the gap between exact string matching (grep) and structural analysis.
"code that handles payment retries"
"where do we validate user permissions"
"functions similar to createUser"
"error recovery logic"
How It Works
1. Chunk
Source files are parsed with tree-sitter into semantically meaningful chunks.
2. Embed
Chunks are converted to vector embeddings using ONNX, Gemini, Ollama, or OpenAI.
3. Store
Vectors are stored in SQLite with sqlite-vec for fast similarity search.
4. Search
Natural language queries are embedded and compared via cosine similarity.
5. Watch
A file watcher auto-syncs the index when files change (debounced, gitignore-aware).
Seamless AI Agent Integration
Auto-detects your AI coding agents and adds VectorCode to their MCP configuration with a single command.
vectorcode install