DingDawg Governance SDK — Universal governance layer for AI agents

Any agent. Any framework. Governed by default.

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What it does

Every AI agent action — writing files, calling APIs, sending emails, modifying data — executes without a receipt. You don't know what ran, what was blocked, or why.

DingDawg Governance adds a pre-execution gate that:

• Blocks policy violations before they execute — fail-closed, not fail-open
• Generates LNN causal traces — interpretable reasoning chain for every decision
• Issues IPFS audit proofs — tamper-evident receipts pinned to distributed storage
• Supports rollback — every governed action carries enough context to reverse it
• Assigns @handle identities — agents get a governed identity (@billing-agent, @hr-screener) with a full action history tied to that handle

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Regulated niches

Built for frameworks where AI agent decisions carry legal weight:

Industry	Regulation
Healthcare	HIPAA — PHI access, treatment decision logging
Insurance / Fintech	State regulations, adverse action documentation
Employment	CO SB 205, EEOC — automated hiring decision audit
Legal	Chain-of-custody, privileged data access controls
Edtech	FERPA — student data access receipts

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Install

npm install dingdawg-governance

pip install dingdawg-loop

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Quick start — Claude Code (MCP config)

Add to ~/.claude/mcp.json or project-level .mcp.json:

{
  "mcpServers": {
    "dingdawg-governance": {
      "command": "npx",
      "args": ["dingdawg-governance"],
      "env": {
        "DINGDAWG_API_KEY": "your-api-key"
      }
    }
  }
}

Without an API key, all tools work locally. Receipts stored at ~/.dingdawg/governance/receipts/.

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Quick start — Python (scheduled governed agents)

from dingdawg_loop import schedule_governed

@schedule_governed(
    agent_id="@data-sync-agent",
    cron="0 * * * *",
    risk_tier="medium"
)
def sync_records():
    # Your agent logic here
    pass

Two lines. Every execution is pre-checked, receipted, and fail-closed. If governance denies, the function does not run.

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MCP tools (6)

Tool	What it does
govern_action	Pre-execution gate — evaluates risk, issues receipt, blocks on violation
audit_trail	Retrieve receipts by agent handle, time range, or receipt ID
compliance_check	Score against EU AI Act, CO SB 205, NIST AI RMF, ISO 42001
rollback_action	Reverse a governed action using its receipt context
register_agent	Assign a governed @handle identity to an agent
ipfs_proof	Retrieve or pin IPFS audit proof for a receipt

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Open-core model

Layer	License	Where
SDK core (govern, audit, compliance)	Apache 2.0	This repo
LNN causal trace engine	Cloud only	dingdawg.com/harness
IPFS proof pinning	Cloud only	dingdawg.com/harness
Team audit trail + cross-agent history	Cloud only	dingdawg.com
Compliance report PDFs (certified)	Paid tier	dingdawg.com/compliance

The core gate runs fully offline. Cloud unlocks team visibility, IPFS pinning, and certified compliance reports.

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Examples

Runnable examples in examples/:

File	What it shows	Regulated use case
01-basic-governance.js	govern_action via MCP JSON-RPC subprocess	Fintech — payment transfer gate
02-python-scheduled-agent.py	@schedule_governed decorator with cron	Healthcare — HIPAA PHI sync
03-crewai-integration.py	CrewAI agents wrapped with governance	Employment — CO SB 205 hiring audit
04-claude-code-mcp-config.json	Drop-in .mcp.json config	All regulated verticals

Each example includes expected output as comments and the governance receipt structure.

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Links

• dingdawg.com — platform, pricing, API keys
• dingdawg.com/docs/integrations — CrewAI, LangGraph, Cursor, Claude Code
• dingdawg.com/harness — LNN engine, IPFS proofs, advanced governance
• dingdawg.com/compliance — CO SB 205 gap report ($199)