knowledge-rag-mcp
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Alternatives to knowledge-rag-mcp
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Related Servers
- AlicenseNot gradedqualityDmaintenanceEnables AI agents to search, deep-read, and build knowledge bases from Markdown, PDF, DOCX, and PPTX documents via MCP tools for retrieval, document navigation, and ingestion.12 npm638MIT
- AlicenseAqualityAmaintenanceEnables AI agents to discover, read, search, and install Markdown-based knowledge (rules, skills, workflows) from a local directory via MCP tools.13270 npm1MIT
- AlicenseNot gradedqualityBmaintenanceEnables agents to retrieve relevant context from local documents via MCP tools, supporting ingestion, semantic search, metadata filtering, and evidence inspection entirely on-device.MIT
- AlicenseNot gradedqualityBmaintenanceEnables coding agents to search local repositories through hybrid keyword and embedding retrieval, read matched chunks, and list indexed repos via MCP, without API keys or cloud services.MIT
- AlicenseNot gradedqualityBmaintenanceProvides AI agents with persistent knowledge storage, enabling them to store, search, and retrieve text, documents, and files using semantic and keyword search via MCP tools.32Apache 2.0
- FlicenseNot gradedqualityDmaintenanceEnables file system operations, web scraping, and AI-powered search through MCP tools for use by LLM agents.1-
TDQS
Scored across 6 tools
Each tool targets a distinct action in the RAG lifecycle: list, status check, preview, connect/index, search, and read. The preview/connect pair shares a resource but their descriptions clearly separate a read-only preview from a confirmed configuration step, so misselection is unlikely.
All tools follow a consistent snake_case verb_noun pattern (list_knowledge_bases, get_setup_status, preview_knowledge_base, connect_knowledge_base, search_knowledge, read_document). No mixed conventions or vague verbs.
Six tools map cleanly onto the setup-to-retrieval workflow with no filler. Each tool earns its place and the count is well-scoped for the domain.
The surface covers setup status, listing, preview, indexing/connect, search, and document read, which handles the core retrieval lifecycle. However, there is no way to disconnect/delete or reindex a knowledge base, leaving lifecycle management gaps an agent may hit.