How do I use kb-rag-mcp?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@kb-rag-mcp search for renewable energy trends and summarize top result" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

kb-rag-mcp

by n1khll

Overview Schema Source Related Servers Discussions Admin

Python

Remote

kb-rag-mcp

Standalone MCP server exposing agentic-RAG tools over a pgvector-backed knowledge base. Designed for public internet deployment (Render) with bearer-token auth; embeddings via Azure OpenAI; LLM/agent side lives in Azure AI Foundry (or any MCP-capable client).

Tools

Tool	Purpose
`kb_search`	Hybrid retrieval (vector + full-text, RRF-fused, MMR-diversified). Returns chunks + citations + confidence.
`kb_get_article`	Full article body by `kb_number` — for drilling into a promising hit.
`kb_list_categories`	Categories + article counts — for scoping a refined search.
`kb_health`	Chunk/article counts + last ingest time — distinguishes "empty KB" from "no match".
`microsoft_learn`	Official Microsoft docs (Microsoft Learn) — external fallback for Microsoft-product questions. One tool, three modes: `search` (default), `code_sample` (commands/scripts, optional `language`), `fetch` (full page by `url`).

The agentic loop lives in the client agent: search the internal KB → check low_confidence → refine / scope by category / fetch full article → answer with citations. For Microsoft-product questions the KB doesn't cover, it falls back to Microsoft Learn (clearly labeled as external).

Microsoft Learn tools proxy the official public MS Learn MCP server (https://learn.microsoft.com/api/mcp, no auth). They cover Microsoft products only (Azure, M365, Windows, Entra, Intune, PowerShell, Graph, …) and fail soft if that endpoint is unreachable. Configurable via MS_LEARN_MCP_URL.

Related MCP server: astra-knowledge-base-mcp

Setup

cp .env.example .env and fill in every value (see comments in that file).
Create the schema: paste scripts/schema.sql into the Neon SQL editor (or psql "$DATABASE_URL" -f scripts/schema.sql).
Ingest articles: python scripts/ingest.py scripts/data/kb_dummy_200.json
Run locally: uvicorn server:app --port 8080

Auth

Every /mcp request needs Authorization: Bearer <key> where <key> is listed in MCP_API_KEYS (comma-separated; one key per client, rotate by adding/removing). No keys configured = all requests rejected. /health is open (used by Render health checks).

Deploy (Render)

Push this directory to a GitHub repo.
Render → New → Blueprint → select the repo (render.yaml is picked up automatically).
Fill the sync: false env vars in the Render dashboard (same values as your local .env).
Your MCP endpoint: https://<service>.onrender.com/mcp

Free-tier note: Render spins the service down after idle; first request after idle takes ~30-60s. Fine for testing; use a paid instance for a client-facing demo.

Smoke test

curl https://<service>.onrender.com/health

curl -X POST https://<service>.onrender.com/mcp \
  -H "Authorization: Bearer $KEY" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

ActivitySlowing

ResponsivenessNo issues

Resources

GitHub Repository

Need Help?

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kb-rag-mcp

Tools

Setup

Auth

Deploy (Render)

Smoke test

Maintenance

Resources

Related MCP Connectors

Related MCP Servers

Hoard

astra-knowledge-base-mcp

porta-rag-mcp

shared-docs-mcp