Rag Knowledge Graph automation via MCP. Includes index document, rag query, add graph edge. ...
Most AI and media services work still happens through a UI a human drives. Rag MCP server moves it into the conversation instead. Rag Knowledge Graph automation via MCP. Includes index document, rag query, add graph edge. ...
RAG + Knowledge Graph MCP — hybrid retrieval with vector embeddings + graph traversal. Citation-aware. MIT.
The server publishes 6 tools. What each one is for:
Well — documented APIProduction-ready — Active maintenancePro — ** $99/mo — Full MCP suite + EU AI Act trackingEnterprise — ** $499/mo — Custom dev + SLA + Dedicated supportDomain — PurposeTier — PriceThe server ships on npm as @smithery/cli, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
This sits in the AI and media services group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Rag's toolset — Well, Production-ready, Pro and 3 more — is a fair guide to whether it matches your workflow. It is maintained by CSOAI-ORG; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| Well | documented API |
| Production-ready | Active maintenance |
| Pro | ** $99/mo — Full MCP suite + EU AI Act tracking |
| Enterprise | ** $499/mo — Custom dev + SLA + Dedicated support |
| Domain | Purpose |
| Tier | Price |
{
"mcpServers": {
"rag-knowledge-graph": {
"command": "npx",
"args": ["-y", "@smithery/cli"]
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.