An MCP server that enables intelligent search and retrieval of QuantConnect documentation by converting PDFs into searchable markdown. It provides tools for context-aware search with TF-IDF scoring and allows for listing and retrieving full document content.
Provides a local MCP server for searching and retrieving documentation from 22+ open-source projects, enabling AI coding assistants to access up-to-date docs without network dependency.
A local MCP server that gives AI coding assistants retrieval access to your personal knowledge base of books, standards, and docs, grounding their answers in sources you trust.
Local documentation search server for AI models using hybrid retrieval (phrase, keyword, vector). Provides MCP tools to search and fetch documentation from bundled or custom doc sets without any external API keys.
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.
