Provides governance for CrewAI agents, wrapping agent actions with pre-execution gates, audit traces, and rollback capabilities to ensure compliance with regulations.
Provides governance for LangGraph agents, integrating pre-execution policy checks, audit trails, and rollback support for regulated workflows.
Any agent. Any framework. Governed by default.
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
Related MCP server: dingdawg-loop
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 |
npm install dingdawg-governancepip install dingdawg-loopAdd 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/.
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
passTwo lines. Every execution is pre-checked, receipted, and fail-closed. If governance denies, the function does not run.
Tool | What it does |
| Pre-execution gate — evaluates risk, issues receipt, blocks on violation |
| Retrieve receipts by agent handle, time range, or receipt ID |
| Score against EU AI Act, CO SB 205, NIST AI RMF, ISO 42001 |
| Reverse a governed action using its receipt context |
| Assign a governed @handle identity to an agent |
| Retrieve or pin IPFS audit proof for a receipt |
Layer | License | Where |
SDK core (govern, audit, compliance) | Apache 2.0 | This repo |
LNN causal trace engine | Cloud only | |
IPFS proof pinning | Cloud only | |
Team audit trail + cross-agent history | Cloud only | |
Compliance report PDFs (certified) | Paid tier |
The core gate runs fully offline. Cloud unlocks team visibility, IPFS pinning, and certified compliance reports.
Runnable examples in examples/:
File | What it shows | Regulated use case |
| Fintech — payment transfer gate | |
| Healthcare — HIPAA PHI sync | |
CrewAI agents wrapped with governance | Employment — CO SB 205 hiring audit | |
Drop-in | All regulated verticals |
Each example includes expected output as comments and the governance receipt structure.
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)
Get the governance audit trail. Returns governance receipts from local storage or cloud API. Free to use.
Inputs: receipt_id, agent_id, time_range, limit.
Quick compliance check against common AI governance frameworks. Free tier: 10 checks per day. Evaluates against EU AI Act, Colorado AI Act, NIST AI RMF, and ISO 42001.
Inputs: system_description (required), framework, deployment_stage.
Govern any AI agent action. Performs capability check + policy evaluation + generates a governance receipt. Returns a receipt proving the action was governed. When API key is set, uses cloud API with local fallback.
Inputs: agent_id (required), action_type (required), action_description (required), target_resource, +2 more.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Scored across 3 tools
Each tool serves a distinct function: audit_trail for retrieving records, compliance_check for framework evaluation, and govern_action for governing an action. No overlap in purposes.
All tool names follow a consistent verb_noun pattern with snake_case: audit_trail, compliance_check, govern_action. Predictable and uniform.
Three tools is ideal for a focused governance server, covering auditing, compliance checks, and action governance without redundancy or bloat.
The set covers core governance workflows (audit, compliance, action governance). Minor gaps exist (e.g., no tool to manage or delete receipts), but the surface is coherent and functional for its scope.
Pre-execution governance for AI agents. Deterministic PASS/FAIL/REVIEW verdicts, replayable proof.
Governed MCP: agent audit, provenance, deterministic checks, and receipt-backed FragGate execution.
Agent-native MCP for governed commerce, x402 payments, paid capabilities, and verifiable receipts.
Agent governance with A2A/Shopify/MCP trust audits, action screening, and decision UI.
