ResultRail by LarryBuildsAI
io.github.LarryLemonBot/resultrail
Pay-per-success public data result packs for AI agents.
Install surfaces
How ResultRail by LarryBuildsAI runs, per the official MCP registry entry.
- streamable-http
https://x402-resource-scanner.vercel.app/resultrail/mcp
Governed execution
How KLA gates calls to ResultRail by LarryBuildsAI once it is connected.
A published policy defines which ResultRail by LarryBuildsAI actions an agent may take and under what conditions. Each call passes through a policy gate at the tool-call boundary. Permitted actions execute, with the policy basis recorded. Flagged actions execute and are sampled for scheduled human review. High-stakes actions pause and route to a named reviewer on the Decision Desk. The call, the policy decision, and any approval are sealed as an evidence record.
KLA also governs the agent frameworks and model providers you already run. See integrations.