Enterprise Internal Knowledge Base: Production-Ready RAG + MCP runs on your own machine — the client starts it, so there is no endpoint to ping. Last commit 26 May 2026.
Production-ready RAG + MCP demo: eval-in-CI merge gate, Langfuse traces, structure-aware chunking.
We read the source, 4 d ago · rules 995398eba69f
What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.
<li><span style="font-size: 16px"><span style="font-family: Arial, Helvetica, sans-serif"><span style="line-height: 115%">Update the “*35% Exemption” field using the dropdown menu. </span></span></span></li>
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Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.
Turn documents into structured, AI-ready data by parsing, enriching, chunking, and embedding.
Text extraction, keyword extraction, language detection, and chunking for RAG
Text extraction, keyword extraction, language detection, and chunking for RAG
Turn any document into a production-ready RAG dataset from Claude, Cursor, or any MCP host.
Minimal RAG-over-a-corpus MCP retrieval: search_knowledge returns cited chunks. Local embeddings.
Academic paper knowledge-base MCP server: PDF ingest, vector search with reranking, KB management.
Offline codebase knowledge graph: 91% token reduction vs naive RAG, plus cross-session agent memory.
Governed graph-native agent memory: knowledge extraction, fusion, hybrid RAG, scoped access tokens.
Answers built from our own checks of this server.