AI Knowledge Base MCP Server
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- FlicenseNot gradedqualityBmaintenanceProvides read-only access to a personal RAG knowledge base, enabling hybrid search, evidence-grounded retrieval with citations, and knowledge gap tracking for LLM agents.-
- AlicenseAqualityCmaintenanceEnables local-first hybrid knowledge retrieval from authorized Markdown and plain-text files, combining full-text and vector search with reranking and traceable source references via a single search tool.1MIT
- AlicenseNot gradedqualityBmaintenanceProvides read-only search and context-pack creation over a local source library, letting AI assistants retrieve relevant excerpts and audit cited quotations.MIT
- AlicenseAqualityAmaintenanceEnables coding agents to query local notes, decisions, docs, and code with hybrid retrieval (BM25 + embeddings + reranking) and get path:line citations. It provides tools like rag_query for full-corpus search and search_knowledge for project-scoped knowledge recall.21MIT
- FlicenseAqualityDmaintenanceEnables AI agents to query a local knowledge graph built from document collections using hybrid search (BM25 + vector fusion) and entity-relationship extraction. Supports privacy-first, offline operation with tools for semantic search, entity graph exploration, and corpus statistics.3-
- FlicenseNot gradedqualityCmaintenanceHybrid semantic search (dense vector + BM25) over local knowledge bases and codebases, exposed as MCP tools for AI agents to search and list knowledge bases.-
TDQS
Scored across 4 tools
Each tool has a distinct purpose: discover for exploration, search for query-based retrieval, get_context for comprehensive context, and get_status for system health. However, get_context and search may cause slight confusion as both involve retrieval.
Tool names are verbs but mix single-word (discover, search) and verb_noun patterns (get_context, get_status). This inconsistency could be improved by normalizing to a single pattern.
Four tools is a minimal but reasonable set for a knowledge base query interface. It covers core functions without bloat, though it could be expanded slightly for more granularity.
The toolset focuses on reading and exploration but lacks write operations (e.g., add, update, delete content). This may hinder agents needing to modify the knowledge base.