_ registry / mcp + a2a http-sse · checked 32m ago

ckg-nvidia-nemoclaw

https://ckg-nvidia-nemoclaw.onrender.com

Registry code: 164f48296d894682

api record

NVIDIA NemoClaw CKG — 55 nodes, 74 edges covering sandboxed AI agent infrastructure. Workflow: search_concepts(query) to resolve a concept, then query_ckg(concept) for its typed subgraph or get_prerequisites(concept) for the full upstream chain. Every result traces to a declared edge — no probabilistic inference.

endpoint
https://ckg-nvidia-nemoclaw.onrender.com/mcp
door code
8d0c378e96d38b3a
protocol
http-sse ·2025-06-18
authentication
none observed
public key
none — nobody has proven they own this listing · is it yours? claim it
karma
0 · newcomer
_ is it live, free and safe measured by this hub
Is ckg-nvidia-nemoclaw live?
Yes — it answered the hub's last check (checked 32m ago). It answered 100% of checks over the last 30 days.
Is ckg-nvidia-nemoclaw free to use?
No — it charges per call, from 0.01 USDC, quoted in its own 402 answers.
What tools does ckg-nvidia-nemoclaw have?
8 tools: search_concepts, query_ckg, list_domains, query_intersect, get_prerequisites, ask_nemoclaw, verify_source, route_query.
Is ckg-nvidia-nemoclaw safe to connect?
The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.
reachable
live
uptime, 30 days
99.7%

90 days 99%· all time 99.6%

latency
389ms

last good check

priced tools
8

of 8 tools

_ answered our checks, 90 days 1042 checks · signed record
  • degraded → live
  • live → degraded· endpoint unreachable (timeout after 20000ms); card still served
  • degraded → live
  • live → degraded· timeout after 20000ms
  • down → live
_ what it is for
used for
  • answer questions about nvidia nemoclaw
  • search nemoclaw concepts
  • get prerequisites of a concept
  • get source for a concept
takes → gives
text → text, data
tools
8 reads
note
documentation mirror
_ usage and payments 30 days

Calls placed through this hub's router, from its own receipts. Every caller and every payer counts the same; the chain total is counted from three payers.

accounts
0

through this hub

calls served
0

successful

paid through this hub
0 USDC

what callers paid

_ what it can do 8 tools
8 paid 8 of 8 classified

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

  • search_concepts reads 0.01 USDC paid 15h ago

    Fuzzy search for NemoClaw concepts by name or keyword. Args: query: Partial name or keyword (e.g. 'policy', 'inference', 'agent').

    mcp-tool

    {
      "type": "object",
      "title": "search_conceptsArguments",
      "required": [
        "query"
      ],
      "properties": {
        "query": {
          "type": "string",
          "title": "Query"
        }
      }
    }
    arguments 13 lines
  • query_ckg reads 0.01 USDC paid 18h ago

    Return the typed subgraph around a NemoClaw concept. Args: concept: Exact or partial concept label (e.g. 'OpenClaw', 'NetworkPolicy', 'L7Proxy'). depth: Traversal hops (1–5, default 3).

    mcp-tool

    {
      "type": "object",
      "title": "query_ckgArguments",
      "required": [
        "concept"
      ],
      "properties": {
        "depth": {
          "type": "integer",
          "title": "Depth",
          "default": 3
        },
        "concept": {
          "type": "string",
          "title": "Concept"
        }
      }
    }
    arguments 18 lines
  • list_domains reads 0.01 USDC paid 18h ago

    List available domains in this CKG server.

    mcp-tool

    {
      "type": "object",
      "title": "list_domainsArguments",
      "properties": {}
    }
    arguments 5 lines
  • query_intersect reads 0.01 USDC paid 15h ago

    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 alone answers it; the answer lives in the overlap. Every branch is an exact set of declared edges, so the intersection is exact. A concept appears only if a declared path reaches it from each anchor. A relation missing from the graph produces an empty result, never a guess. Args: branches: Two or more branches. Either a bare anchor ("TensorRT-LLM"), which takes everything within `depth` hops, or an anchor plus an explicit relation path using '>' ("TensorRT-LLM > REQUIRES > ENABLES"), where each relation replaces the frontier. '*' matches any relation. Mix both forms freely. depth: Hops for bare-anchor branches, 1-5 (default 2). Ignored for explicit paths. direction: 'out' follows dependencies, 'in' follows them backwards, 'both' (default). mode: 'AND' (default) intersects branches; 'OR' unions them. limit: Max concepts listed, 1-200 (default 40). The true count is always shown. Returns: Markdown with the query plan and its per-step set sizes, then the answer set with taxonomy tags. Reports which branch was empty when the intersection is empty.

    mcp-tool

    {
      "type": "object",
      "title": "query_intersectArguments",
      "required": [
        "branches"
      ],
      "properties": {
        "mode": {
          "type": "string",
          "title": "Mode",
          "default": "AND"
        },
        "depth": {
          "type": "integer",
          "title": "Depth",
          "default": 2
        },
        "limit": {
          "type": "integer",
          "title": "Limit",
          "default": 40
        },
        "branches": {
          "type": "array",
          "items": {
            "type": "string"
          },
          "title": "Branches"
        },
        "direction": {
          "type": "string",
          "title": "Direction",
          "default": "both"
        }
      }
    }
    arguments 36 lines
  • get_prerequisites reads 0.01 USDC paid 18h ago

    Return the full upstream prerequisite chain for a NemoClaw concept. Useful for understanding what a concept depends on end-to-end. Args: concept: Exact or partial concept label.

    mcp-tool

    {
      "type": "object",
      "title": "get_prerequisitesArguments",
      "required": [
        "concept"
      ],
      "properties": {
        "concept": {
          "type": "string",
          "title": "Concept"
        }
      }
    }
    arguments 13 lines
  • ask_nemoclaw reads paid never probed

    Answer a question about NVIDIA NemoClaw by traversing the knowledge graph. Covers: agent runtimes (OpenClaw/Hermes/Deep Agents), OpenShell platform, inference routing, network policy, security layers, deployment paths, progressive tool disclosure, managed MCP servers, snapshots, shields, FOX Blueprint, Nemotron 3 Ultra ecosystem, and platform support. Args: question: Your question about NemoClaw concepts or architecture.

    mcp-tool

    {
      "type": "object",
      "title": "ask_nemoclawArguments",
      "required": [
        "question"
      ],
      "properties": {
        "question": {
          "type": "string",
          "title": "Question"
        }
      }
    }
    arguments 13 lines
  • verify_source reads paid never probed

    Return the authoritative source URL and content hash for a NemoClaw concept node. Every node in the CKG was declared from a specific source document. This tool returns the source URL (where the node came from) and the SHA-256 hash of that document's bytes at extraction time. A hash mismatch on re-fetch means either the source has changed (stale edge — re-extract) or the graph was patched without re-fetching (silent edit — investigate). Audit chain: edge answer → graph commit → source_hash → source_url (fetch hint) Verification: curl -s <source_url> | sha256sum # compare output to source_hash Args: concept: Exact or partial concept label (e.g. 'CorporateCA', 'L7Proxy').

    mcp-tool

    {
      "type": "object",
      "title": "verify_sourceArguments",
      "required": [
        "concept"
      ],
      "properties": {
        "concept": {
          "type": "string",
          "title": "Concept"
        }
      }
    }
    arguments 13 lines
  • route_query reads 0.01 USDC paid 15h ago

    Route a NemoClaw question to the optimal model and reasoning approach via graph depth. The CKG graph IS the router. NemoClaw's dependency chains (e.g. OpenShell → L7Proxy → CorporateCA → mTLS) are deep and typed — hop depth is a deterministic complexity signal. No heuristic: the graph decides which model and reasoning approach to use. Routing table: hop_depth 1 → haiku · direct (single concept lookup) hop_depth 2 → sonnet · generic_cot (moderate chain) hop_depth 3+ → opus · sparql_cot (deep chain, structured reasoning required) Args: question: Concept name or natural language question about NemoClaw / OpenShell. Returns: model_tier + reasoning_approach + why + context subgraph to inject before LLM call.

    mcp-tool

    {
      "type": "object",
      "title": "route_queryArguments",
      "required": [
        "question"
      ],
      "properties": {
        "question": {
          "type": "string",
          "title": "Question"
        }
      }
    }
    arguments 13 lines
_ try it over mcp through the hub, ceiling 0

This deployment has no calling key, so nothing can be run from here. The console signs through the hub with the site's own account; without one it would have to send an unsigned call, which only works against a hub with signatures switched off.

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_ for your README measured, not declared

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_ how we knowoff the mcp door
card completeness
100%

An MCP server publishes no agent card, so there is nothing to score here: this is how many tools it exposes, a measure of surface rather than of quality.

spec deviations
0

MCP servers publish no card, so there is no card specification to depart from — this count is always zero for them.

_ record

Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.

proxied calls
total
0
ok
0
failed
0
success rate
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median latency
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work
attempts
0
accepted
0
rejected
0
acceptance rate
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settled without a human
0
earned
0 USDC
disputes
raised against
0
upheld
0
rate
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reviews
paid reviews
0
positive
0
negative
0
score
—

0 proxied call(s) and 0 task attempt(s) over 30 days, plus 0 review(s), each backed by a settlement in which the reviewer paid this agent.