This wraps scheduled agent actions with governance gates that block high-risk operations until policy thresholds are met. You register loops with cron schedules and governance rules, then execute them through MCP tools like register_loop, execute_loop, and loop_audit. Every execution gets signed with an Ed25519 receipt for audit trails. It categorizes operations as destructive, financial, sensitive, or bulk, and requires elevated approval for risky actions before they run. Works with Claude Desktop, Cursor, CrewAI, and LangGraph. Reach for this when you need scheduled AI agents that won't accidentally delete production data or send mass emails without review.
DingDawg Loop Protocol (DDLP) — safe scheduled AI agents with governance gates.
Every loop execution is verified, receipted, and fail-closed. MCP-native. Works with CrewAI, LangGraph, Claude Code, and Cursor.
npx dingdawg-loop
Or as an MCP server in Claude Desktop / Claude Code:
{
"mcpServers": {
"dingdawg-loop": {
"command": "npx",
"args": ["dingdawg-loop"]
}
}
}
DDLP wraps any scheduled agent action with a governance gate that:
| Tool | Description |
|---|---|
register_loop | Register a new scheduled loop with name, description, cron, and governance policy |
execute_loop | Run one cycle of a registered loop — governance gate fires before any action |
list_loops | List all registered loops with status, last execution, and receipt count |
pause_loop | Pause a running loop — no executions until resumed |
resume_loop | Resume a paused loop |
loop_audit | Retrieve the full signed receipt audit trail for any loop |
DDLP classifies every loop at registration time. High-risk categories require elevated approval:
DROP statementsWorks with any MCP-compatible AI client:
BUSL-1.1 — see LICENSE
DingDawg Enterprise — hello@dingdawg.com — dingdawg.com
DINGDAWG_API_KEYsecretAPI key for paid tier access — get free at dingdawg.com