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supernova-mcp-rag
A practical POC demonstrating how to build and run a local MCP server with Retrieval-Augmented Generation (RAG) for semantic search over internal documentation. Leverages Node.js, TypeScript, Hugging Face embeddings, and an in-memory vector store to enable fast, context-aware answers in tools like Cursor.
1stars
3forks
TypeScript
huggingfacelangchainmcpmcp-ragmcp-rag-servermcp-servermcp-server-setupmodel-context-protocolragretrieval-augmented-generationsemantic-search
Quality signals
StaleNo testsNo CIThin docsNo licenseNew
InstallMCPRun via npx (Node)
Universal installANY TOOL
$ npx skillcity@latest shabib87/supernova-mcp-ragAuto-detects the skill or MCP server in this repo and installs it for Claude Code, Codex, Cursor, Cline, OpenCode, Gemini CLI, Anti-Gravity, OpenClaw and Hermes.
Requires Node.js 18+ (ships with npx).
Or install manually
npx -y supernova-mcp-rag
MCP Configuration
Add this to your claude_desktop_config.json
{
"mcpServers": {
"supernova-mcp-rag": {
"command": "npx",
"args": [
"-y",
"supernova-mcp-rag"
]
}
}
}Loading README…
Ask a simulated agent to run this skill. It loads the real SKILL.md and reasons over your task with NVIDIA.
supernova-mcp-rag — sandboxAI sandbox
Pick a quick prompt below or type your own — watch the agent execute this skill step by step.
guest@skillcity:~$Try a prompt