Enables semantic search over local Markdown documentation using hybrid retrieval combining embeddings, keyword search, and graph traversal with automatic file watching and zero-configuration setup.
Provides hybrid search over local markdown knowledge bases using BM25 keyword search and vector semantic search. Enables indexing, querying, and retrieving markdown documentation with dual-mode support for local and remote agents.
Semantic search over any markdown corpus using local embeddings. Provides tools to search, reindex, and get index stats, with results including file paths, line numbers, and header breadcrumbs.
Enables semantic search over a software project's Markdown and text documentation by indexing document chunks in Qdrant and exposing retrieval through MCP tools.
Enables semantic search through markdown documentation in code repositories using AI embeddings. Provides intelligent document chunking and similarity-based search to help users find relevant documentation based on meaning rather than just keywords.