Knowledge Assistant MCP Server
Related Servers
Alternatives to Knowledge Assistant MCP Server
No user-submitted related servers found.
Related Servers
- AlicenseAqualityAmaintenanceA multi-agent Retrieval-Augmented Generation system exposed as an MCP server. Ask a question and a LangGraph pipeline plans the retrieval, pulls evidence from a pgvector knowledge base, optionally augments it with live web research, drafts a cited answer, and then self-critiques it for grounding — revising until the answer is supported by the sources.31MIT
- AlicenseNot gradedqualityBmaintenanceMCP server that coordinates multiple AI specialists (SQL database, document RAG, and web research) using LangGraph, routing each question to the relevant agents and synthesizing their responses into a single answer with honest confidence flags.MIT
- FlicenseNot gradedqualityBmaintenanceMCP server for a modular RAG system that enables natural language question answering over enterprise documents with intent-aware routing, adaptive retrieval, and citation-backed responses.-
- FlicenseNot gradedqualityBmaintenanceMCP server for a shared Postgres-backed knowledge base with hybrid retrieval and agentic RAG, enabling coding agents to upload, search, and ask questions over documents with cited answers.-
- AlicenseNot gradedqualityBmaintenanceMCP server providing tools for entity extraction, query refinement, and relevance checking to build Agentic RAG applications.MIT
- AlicenseNot gradedqualityAmaintenanceMCP server for local RAG over personal notes, PDFs, and documents, enabling plain-English querying and hybrid search with multi-hop context expansion.MIT
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose: query_knowledge_base runs the full RAG pipeline and returns a proposed answer, search_knowledge_base performs raw retrieval only, approve_or_edit_answer handles the human-in-the-loop review step, and add_documents ingests new content. Although query and search both access the knowledge base, their outputs and workflows are fundamentally different and clearly described.
All tool names follow a consistent verb_noun pattern in snake_case: query_knowledge_base, approve_or_edit_answer, add_documents, search_knowledge_base. The naming is uniform and predictable, with no mixed conventions or ambiguous verbs.
With exactly 4 tools, the server is well-scoped for its purpose. Each tool addresses a distinct stage of the knowledge assistant workflow (ingestion, retrieval, synthesis, and review), and the count feels neither sparse nor bloated for the domain.
The core workflow is covered: add documents, search raw chunks, generate a proposed answer, and approve/request edits. However, there are minor gaps in document lifecycle management—no tools for deleting, updating, or listing documents—which could force workarounds in some use cases.