Provides tools for ingesting documents into a local vector database and retrieving relevant information via semantic search, enabling retrieval-augmented generation for MCP clients.
Enables users to ingest documents, run retrieval-augmented queries with dense/sparse search and reranking, and inspect ingestion/query traces and evaluation results through MCP tools.
Enables a single MCP server for interacting with multiple vector databases through pluggable backends, starting with Pinecone. It supports schema-aware index management, upserts, hybrid search, embeddings, TTL conventions, and namespace operations.