Enables AI agents to query and manage a document knowledge base via MCP, with RAG-powered search and grounded answers with citations.
Emerging. Nothing concerning found — the project is young, and grades cap until reputation is earned through real adoption. Grades reflect the full trust pyramid: code, verification depth, and reputation. New projects cap at C until adoption is earned.
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process.env. You'll be asked to provide them before it can run. Since this is a local server, you set these in your own MCP client configuration and they stay on your machine. The secret label means the value is sensitive, not that the server mishandles it.RAG_CHUNK_SIZE— 600 Text chunk size (chars)RAG_CHUNK_OVERLAP— 120 Overlap between chunksRAG_EMBEDDING_MODELRAG_CHROMA_DIR— .chroma Vector store pathRAG_COLLECTION— docs ChromaDB collection nameRAG_DATA_DIR— data Document directoryLLM_PROVIDER— OpenAI fallback: Set =openai and OPENAI_API_KEY=sk-...OLLAMA_URLOLLAMA_MODEL— Ollama (default): Local, free, no API key. Set =llama3.2.OPENAI_API_KEY— OpenAI fallback: Set LLM_PROVIDER=openai and =sk-...OPENAI_MODEL— gpt-4o-mini OpenAI model name[](https://m8ven.ai/mcp/zyay-mcp-rag-bridge-1icfa1)?variant=verified to the badge URL.Vetting this one by hand? Tool Check is an MCP that scores other MCPs. Add it once and ask Claude, ChatGPT, or any MCP client to grade a server, surface CVEs, check the publisher, and suggest safer alternatives — before you install.
https://m8ven.ai/api/mcp/tool-check