Local FAISS vector database for RAG with document ingestion, semantic search, and MCP prompts.
A Model Context Protocol (MCP) server that provides local vector database functionality using FAISS for Retrieval-Augmented Generation (RAG) applications. Local Vector Storage: Uses FAISS for efficient similarity search without external dependencies Document Ingestion: Automatically chunks and embeds documents for storage Semantic Search: Query documents using natural language with sentence…
Inferred from the transports this listing declares (stdio). A client not listed here hasn’t been ruled out — it just isn’t something Forge can confirm.
Verification confirms publisher identity (repo ownership), not code safety. The security scan covers known CVEs and suspicious install scripts.
Forge read 0 source files from the published package tarball and matched no MCP tool registrations. Extraction is pattern-based over shipped source: a server that builds its tool list at runtime, or that ships only bundled or minified code, registers nothing this can see. Treat it as “not detected”, not as “exposes none”.
A Model Context Protocol (MCP) server that provides local vector database functionality using FAISS for Retrieval-Augmented Generation (RAG) applications. Local Vector Storage: Uses FAISS for efficient similarity search without external dependencies Document Ingestion: Automatically chunks and embeds documents for storage Semantic Search: Query documents using natural language with sentence embeddings Persistent Storage: Indexes and metadata are saved to disk MCP Compatible: Works with any…
Forge's dependency resolver reads npm metadata only, so this PyPI package has no resolved tree. That is a gap in coverage, not a clean bill of health.