ckg-nvidia-guardrails 0.1.0

NeMo Guardrails as a traversable knowledge graph — 50 nodes, MCP-native, free

ckg-nvidia-guardrails

NeMo Guardrails as a traversable knowledge graph.

50 nodes · MCP-native · free · Graphify.md

pip install ckg-nvidia-guardrails
uvx ckg-nvidia-guardrails

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The problem this solves

NeMo Guardrails rails govern conversation flow — but the tool fleet executes entirely outside the railed channel. There is no mutual visibility between config.yml rails configuration and tool/action bindings.

This means:

• Auto-approved shell-capable tools bypass guardrails entirely
• Outgoing responses from tool calls leave un-railed
• Rails config and tool config exist as separate files with no declared relationship

This knowledge graph maps those relationships explicitly. Query the Tool Authorization Gap node to traverse what's railed vs what isn't:

query_ckg('Tool Authorization Gap', 'nvidia-guardrails', 3)

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What's covered (50 nodes)

Domain	Nodes
Rails Architecture	NeMo Guardrails · Dialog Flow Manager · Input/Output/Dialog/Retrieval Rails
Colang Language	Colang 1.0 · Colang 2.0 · Flow · Message · Context Variables · Event System
Configuration	config.yml · Models · Rails · Actions · Prompts · Generation Options
Actions & Tools	Custom Actions · Python Actions · Action Server · Tool Bindings · Tool Authorization Gap
Rail Implementations	Jailbreak Detection · Hallucination Detection · Sensitive Data · Moderation · Topical Rails
Integrations	LangChain · LlamaIndex · NIM · Custom LLM Provider · OpenAI-Compatible API
Observability	Logging · Colang Tracing · Rail Testing · NemoGuardrails CLI
Deployment	Guardrails Server · REST API · Streaming Support

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MCP tools

Tool	Description
list_domains()	List available domains
search_concepts(query)	Find concepts by keyword
query_ckg(concept, depth)	Traverse from any concept outward
get_prerequisites(concept)	Full upstream dependency chain
ask_guardrails(question)	Natural-language Q&A (requires local Ollama)

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Add to Claude Desktop

{
  "mcpServers": {
    "nvidia-guardrails": {
      "command": "uvx",
      "args": ["ckg-nvidia-guardrails"]
    }
  }
}

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Benchmark

11× fewer tokens than RAG · F1 0.471 vs RAG 0.123 · 269 tokens/query vs 2,982

Full paper: github.com/Yarmoluk/ckg-benchmark/blob/main/paper/main.pdf

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EVAL

benchmark: ckg-benchmark v0.6.2
dataset: huggingface.co/datasets/danyarm/ckg-benchmark
benchmarked: false
rag_baseline_f1: 0.123
graphrag_baseline_f1: 0.120
mean_tokens: 269
paper: github.com/Yarmoluk/ckg-benchmark/blob/main/paper/main.pdf

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