Enables document ingestion, semantic search, and retrieval-augmented generation via MCP tools and REST API, using vector embeddings and intelligent chunking.
An MCP server that gives AI coding assistants access to up-to-date API documentation via RAG by crawling documentation sites, indexing them into a vector store, and enabling semantic queries.
A self-hostable, MCP-native RAG pipeline that ingests, indexes, and serves data, enabling AI agents to scan codebases for prioritized findings and integrate with CI workflows.
Enables vector search and document retrieval, extraction and chunking of any file into Markdown, and private deep research generation through Vectorize pipelines. It connects MCP clients such as Claude, Cursor, and VS Code to these Vectorize APIs.