Enterprise DNA
M MCP Servers Developer low

IgorGanapolsky/ThumbGate

by Various

Agent governance for ThumbGate: ๐Ÿ‘/๐Ÿ‘Ž become Pre-Action Checks that block repeat mistakes before code, money, or customer systems change.

I

MCP

IgorGanapolsky/ThumbGate

Added 1 June 2026

#agent-reliability #ai-agents #ai-cost-optimization #ai-safety #amp #claude-code #codex #cursor

Overview

ThumbGate is a JavaScript tool that uses thumbs up and thumbs down as pre-action checks to block repeated mistakes before code, money, or customer system changes. It applies agent governance by capturing past feedback and preventing similar errors from occurring again.

Best for

Best for
Teams using agent-driven workflows who want to prevent repeat mistakes with minimal friction

Use cases

  • Preventing repeated deployment failures by applying thumbs-down checks
  • Enforcing approval gates for automated code changes
  • Blocking costly rollbacks by capturing past mistakes as pre-action checks

Notes

ThumbGate is a JavaScript tool that uses thumbs up and thumbs down as pre-action checks to block repeated mistakes before code, money, or customer system changes. It applies agent governance by capturing past feedback and preventing similar errors from occurring again.

21 stars on GitHub. Last updated 2026-06-01. Licensed MIT.

Use cases

  • Preventing repeated deployment failures by applying thumbs-down checks
  • Enforcing approval gates for automated code changes
  • Blocking costly rollbacks by capturing past mistakes as pre-action checks

Pros

  • Lightweight and simple to integrate into agent workflows
  • Directly addresses the common problem of repeat errors
  • Minimal overhead with a clear binary feedback mechanism

Cons

  • Limited to binary thumbs up/down, lacking nuanced policy support
  • Relies on consistent manual feedback which may not scale
  • Not suited for complex or multi-step governance requirements

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Lightweight and simple to integrate into agent workflows
  • Directly addresses the common problem of repeat errors
  • Minimal overhead with a clear binary feedback mechanism

Cons

  • Limited to binary thumbs up/down, lacking nuanced policy support
  • Relies on consistent manual feedback which may not scale
  • Not suited for complex or multi-step governance requirements