A secure, vector-based memory server for Claude Desktop using sqlite-vec and sentence-transformers
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# Vector Memory MCP Server A **secure, vector-based memory server** for Claude Desktop using `sqlite-vec` and `sentence-transformers`. This MCP server provides persistent semantic memory capabilities that enhance AI coding assistants by remembering and retrieving relevant coding experiences, solutions, and knowledge. ## ✨ Features - **🔍 Semantic Search**: Vector-based similarity search using 384-dimensional embeddings - **🏷️ Semantic Normalization**: Auto-merge similar tags, normalize categories, structured colon tags - **📊 IDF Tag Weights**: Frequency-based weighting for improved search relevance - **💾 Persistent Storage**: SQLite database with vector indexing via `sqlite-vec` - **🔒 Security First**: Input validation, path sanitization, and resource limits - **⚡ High Performance**: Fast embedding generation with `sentence-transformers` - **🧹 Auto-Cleanup**: Intelligent memory management and cleanup tools - **📈 Rich Statistics**: Comprehensive memory database analytics - **🔄 Automatic Deduplication**: SHA-256 content hashing prevents storing duplicate memories - **🧠 Smart Cleanup Algorithm**: Prioritizes memory retention based on recency, access patterns, and importance ## 🛠️ Technical Stack | Component | Technology | Purpose | |-----------|------------|---------| | **Vector DB** | sqlite-vec | Vector storage and similarity search | | **Embeddings** | sentence-transformers/all-MiniLM-L6-v2 | 384D text embeddings | | **Normalization** | Semantic similarity + guards | Tag/category auto-merge | | **MCP Framework** | FastMCP | High-level tools-only server | | **Dependencies** | uv script headers | Self-contained deployment | | **Security** | Custom validation | Path/input sanitization | | **Testing** | pytest + coverage | Comprehensive test suite | ## 📁 Project Structure ``` vector-memory-mcp/ ├── main.py # Main MCP server entry point ├── README.md # This documentation ├── requirements.txt …
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