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NVIDIA AI CKG

io.github.Yarmoluk/ckg-nvidia-ai · v0.16.4

NVIDIA AI knowledge graphs — 20 domains. 4x F1, 11x fewer tokens, SHA-256 provenance. MCP-native.

Connect Remote server

Terminal
claude mcp add --transport http ckg-nvidia-ai https://ckg-nvidia-ai.onrender.com/mcp
~/.cursor/mcp.json
{
  "mcpServers": {
    "ckg-nvidia-ai": {
      "url": "https://ckg-nvidia-ai.onrender.com/mcp"
    }
  }
}
.vscode/mcp.json
{
  "servers": {
    "ckg-nvidia-ai": {
      "type": "http",
      "url": "https://ckg-nvidia-ai.onrender.com/mcp"
    }
  }
}
Claude Desktop
Settings > Connectors > Add custom connector
URL: https://ckg-nvidia-ai.onrender.com/mcp

Tools 9 found in our last check

  • list_domains

    List all 21 NVIDIA AI domains available in this knowledge graph.

  • search_concepts

    Find concepts in a NVIDIA AI domain by keyword. Args: query: Search term — e.g. 'inference', 'sandbox', 'quantization', 'guardrails'. domain: Domain name from list_domains() — e.g. 'nvidia-nim', 'nvidia-openshell'.

  • query_ckg

    Traverse the NVIDIA knowledge graph from a concept — prerequisites and dependents. Args: concept: Concept name (partial match supported) — e.g. 'TensorRT', 'NIM', 'Isaac Lab'. domain: Domain name from list_domains() — e.g. 'nvidia-tensorrt-triton', 'nvidia-isaac'. depth: Travers…

  • get_prerequisites

    Return the full ordered prerequisite chain for a concept — everything to learn first. Args: concept: Target concept — e.g. 'Speculative Decoding', 'Isaac Lab', 'NeMo Guardrails'. domain: Domain name from list_domains().

  • ask_nvidia

    Ask a natural-language question answered by Qwen grounded on the NVIDIA CKG. Requires Ollama running locally with a Qwen model pulled: ollama pull qwen2.5:14b Override model: NVIDIA_CKG_MODEL env var (default: qwen2.5:14b) Override host: NVIDIA_CKG_OLLAMA env var (default: http:…

  • list_ecosystem

    Discover other CKG packages for adjacent domains — finance, healthcare, legal, and more.

  • route_query

    Route an NVIDIA AI question to the optimal model and reasoning approach via graph depth. The CKG graph IS the router — hop depth is a deterministic complexity metric. Deeper NVIDIA prerequisite chains (CUDA → TensorRT → TensorRT-LLM → NIM) require more capable models. No heurist…

  • verify_source

    Return the source URL and SHA-256 content hash for any NVIDIA AI concept node. Audit chain: edge answer → graph commit → source_content_hash → source_url (fetch hint). Verification: curl -s <source_url> | sha256sum # compare to source_hash Args: concept: Concept label (partial m…

  • query_intersect

    Answer a conjunctive query: concepts reachable from EVERY anchor at once (A AND B). query_ckg walks outward from one concept. This intersects the reachable sets of two or more, which is the shape of most real questions — "the component that satisfies A AND applies to B". Neither…

Details

Endpointhttps://ckg-nvidia-ai.onrender.com/mcp (Streamable HTTP)
Package[email protected] (PYPI, stdio)
First published29 Jul 2026
Last updated29 Jul 2026
Registry nameio.github.Yarmoluk/ckg-nvidia-ai

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