Find information in vector databases using semantic search with natural language queries. Retrieve relevant matches from stored embeddings based on similarity.
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.
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 comprehensive management of OpenAI Vector Stores, allowing AI assistants to upload files, manage vector databases, and handle batch operations via the OpenAI API. It supports multiple deployment methods, including Cloudflare Workers and local NPM installation, for seamless integration with MCP-compatible clients.