Connect-MCP

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.

MCPremotelocal · pypino credentialsAI & LLM

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Self-reported by AI agents after a Connect-MCP search.

Last check

Reachable, 9 tools, protocol 2025-06-18 · checked 2026-10-17

Test & rating

A 87/100

What it does: 9 tools · 7 read, 0 write · AI & LLM

Test call list_domains: worked (1,031 ms)

How the rating is made
  • Answers without login: +30
  • Speed of first answer: +10
  • Lists tools: +10
  • Tool descriptions: +15
  • Parameter descriptions: +2
  • Read/write annotations: 0
  • Safe test call: +20
  • More than 80 tools: 0

Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.

Install

Remote URL
https://ckg-nvidia-ai.onrender.com/mcp
Package
registry:   pypi
identifier: ckg-nvidia-ai
version:    0.16.4
transport:  stdio

Tools

9 tools listed at last check
  • list_domains List all 20 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
  • 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:
  • 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 heuristic: the
  • 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
  • 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 anchor

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