Generate a vector index on a specified field within a table to enable efficient vector similarity searches in Baidu Vector Database. Supports HNSW, HNSWPQ, HNSWSQ index types and L2, COSINE, IP metrics.
Find information in vector databases using semantic search with natural language queries. Retrieve relevant matches from stored embeddings based on similarity.
Perform vector similarity searches in Baidu Vector Database by combining vector matching and scalar attribute filtering for precise data retrieval. Specify table, vector, and optional filters to get relevant results efficiently.
PG-MCP is an HTTP server implementation that enables AI systems to interact with PostgreSQL databases via MCP, providing tools for querying, connecting to multiple databases, and exploring schema resources. The system enriches context by extracting table/column description from database catalogs.
A secure vector-based memory server that provides persistent semantic memory for AI assistants using sqlite-vec and sentence-transformers. It enables semantic search and organization of coding experiences, solutions, and knowledge with features like auto-cleanup and deduplication.
Provides local vector-based semantic memory storage for AI assistants to persist context and decisions across sessions using local embeddings and LanceDB. It enables private semantic search and session handoff capabilities to maintain long-term project context.