OpenChainGraph Suite · CONTRACT A3 · arch #5

Agentic AI & GPAI Governance

Note (dated 2026-08-04): a chain composes independent computations performed in an analytical order. No step's output is carried into the next step by the execution model; each step computes from its own declared inputs. This is true of every chain on this site, including chains whose per-step copy below reads as a data handoff.

W-D. Agentic-AI autonomy + GPAI/systemic-risk classification (ART-67, Arts 53-55 IN FORCE 2 Aug 2025) -> agent identity & authorization (art-04) -> agent/MCP self-attestation (art-33). Governs the autonomous AI agents that transact on the Wave-14 runtime: the reflexive tie between AINumbers' agent rails and AI governance.

OpenChainGraph · 3 Steps infrastructure mandate Hash-Anchored §4 chain_depth:3 Client-Side · Zero PII
Chain Topology — Agentic AI Risk & GPAI Governance Classifier → Agent Identity & Authorization Attestation Checker → MCP Server Self-Attestation Pack
§4 Execution Hash · Chain Definition Anchor
execution_hash:computing…
Chain Stages · 3 Steps
1 ROOT · D0 node
Agentic AI Risk & GPAI Governance Classifier art-67-agentic-ai-risk-classifier
governance_tier and gpai_class (H1) feed the identity checker
MCP Call · classify_agentic_ai_risk
{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "classify_agentic_ai_risk",
    "arguments": {}
  },
  "id": 1
}
https://mcp.ainumbers.co/mcp
↓
2 D2 node
Agent Identity & Authorization Attestation Checker art-04-agent-identity-attestation-checker
attestation verdict (H2) feeds the self-attestation pack
MCP Call · check_agent_attestation
{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "check_agent_attestation",
    "arguments": {}
  },
  "id": 1
}
https://mcp.ainumbers.co/mcp
↓
3 TERMINAL · D3 node
MCP Server Self-Attestation Pack art-33-mcp-server-self-attestation-pack
Exports composite agentic-governance artifact with execution_hash (H3), final stage
MCP Call · attest_mcp_server
{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "attest_mcp_server",
    "arguments": {}
  },
  "id": 1
}
https://mcp.ainumbers.co/mcp
Export Artifacts
Download the §4 chain definition artifact (hash-anchored composite JSON) or the §13.11 W3C Verifiable Credentials view. Both derive from the chain definition — no new hash is minted. Available after hash computation.

Ask your agent

Copy this paragraph into Claude, OpenClaw, or any MCP-aware agent to run this whole workflow on the server and check one field that answers a real question.

Question: Procurement wants to swap the agent foundation model for a proprietary one. What changes in the resulting GPAI classification and obligation set?
Run the AINumbers MCP tool `run_chain` with {"chain":"ai-governance-gpai-agentic"} and read `art-67-agentic-ai-risk-classifier.gpai_class`.
Re-run with `inputs` for `art-67-agentic-ai-risk-classifier`, reusing the values that result echoed, with `model` changed so type is proprietary, systemic_designation no. Compare the same field.
Verify: call `verify_execution_hash` (https://mcp.ainumbers.co/mcp) with `claimed_hash` set to `composite_execution_hash` and the full `composite_artifact`.
Ledger, for a human re-check: https://ledger.ainumbers.co/
PII rule: send synthetic or anonymised inputs only. The MCP server runs these kernels and logs no payloads.
Chain page: https://ainumbers.co/chaingraph/chains/ai-governance-gpai-agentic.html