# ThumbGate — Self-Improving Firewall for Your AI Agents
# https://thumbgate.ai
# https://github.com/IgorGanapolsky/ThumbGate
# https://www.npmjs.com/package/thumbgate

> ThumbGate is the self-improving firewall that prevents expensive AI mistakes
> before they happen. It checks risky commands, file edits, deploys, payments,
> API calls, and other agent actions before execution. Explicit feedback becomes
> reviewable local lessons; relevant lessons are re-ranked for each proposed
> action; repeated negative patterns can promote from warning to blocking gates;
> stale auto-promoted gates expire; and stale lessons archive. ThumbGate improves
> the external control layer without changing model weights.

## Store story

ThumbGate: the self-improving firewall for AI agents. Every approval teaches it what to allow, block, or escalate next time. Self-improving under your control—not silent policy rewrite. Hermes Mobile is the control surface; ThumbGate is the learning safety layer inside it.

## What ThumbGate solves

- AI coding agents repeat costly mistakes across sessions
- Bad commands, destructive SQL, risky deploys, unsafe publishes, and API mistakes are expensive after execution
- CLAUDE.md and .cursorrules files are suggestions agents can ignore
- No memory between sessions means no learning from corrections
- Teams have no shared safety rules across developers
- AI crawlers and agents create machine traffic without proving buyer intent; teams need AI-discoverable proof plus runtime gates before internal agents act

## How it works

1. A developer records explicit feedback with the action and outcome context
2. ThumbGate stores the feedback as a reviewable local lesson
3. Relevant lessons are re-ranked for the proposed action
4. Repeated negative patterns can promote from warning to blocking gates
5. PreToolUse hooks return allow, warn, or deny before the next matching action
6. Stale auto-promoted gates expire and stale lessons archive

## Agentic development cycle fit

ThumbGate maps to Guide, Generate, Verify, Solve by adding a pre-action execution gate:

- Guide: feedback and policies become concrete rules
- Generate: agents still produce plans, edits, and tool calls
- Verify: risky actions require evidence before execution
- Solve: blocked failures become reusable lessons and prevention gates

## Who it's for

- Developers using Claude Code, Cursor, Codex, Gemini CLI, or any MCP-compatible agent
- Engineering teams that need shared agent safety rules
- Anyone tired of re-correcting their AI coding assistant
- Solo operators who want Pro dashboard proof for blocked mistakes and DPO exports

## Install

```
npx thumbgate init --agent claude-code
```

## Pricing

- ChatGPT App / GPT Action: https://thumbgate.ai/chatgpt-app
- Free GPT: advice, checkpointing, and setup help in ChatGPT
- Codex Plugin: https://thumbgate.ai/codex-plugin
- Free local CLI: 2 captures/day, 10 total captures, up to 3 active auto-promoted prevention rules, and local Pre-Action Checks after install (recall and lesson search are Pro-only)
- Pro: $19/mo or $149/yr — personal enforcement proof, local dashboard, check debugger, DPO export, synced lessons/rules across machines, and review-ready exports
- Enterprise: custom pricing, scoped after intake — shared hosted lesson database, org-wide dashboard, GCP/DFCX guardrails, VPC gating, and white-glove workflow hardening sprints

## Links

- Home: https://thumbgate.ai/
- Pricing: https://thumbgate.ai/pricing
- Pro checkout: https://thumbgate.ai/checkout/pro
- Agent discovery: https://thumbgate.ai/.well-known/mcp.json
- Progressive tool index: https://thumbgate.ai/.well-known/mcp/tools.json
- Context footprint report: https://thumbgate.ai/.well-known/mcp/footprint.json
- Headroom context compression guardrails: https://thumbgate.ai/guides/headroom-context-compression-guardrails
- Sovereign coding model guardrails: https://thumbgate.ai/guides/sovereign-coding-model-guardrails
- Agentic web governance: https://thumbgate.ai/guides/agentic-web-governance
- AI Mode ads and agent governance: https://thumbgate.ai/guides/ai-mode-ads-agent-governance
- MCP tool governance: https://thumbgate.ai/guides/mcp-tool-governance
- AI agent pre-action approval gates: https://thumbgate.ai/guides/ai-agent-pre-action-approval-gates
- Agent skills: https://thumbgate.ai/.well-known/mcp/skills.json
- MCP applications: https://thumbgate.ai/.well-known/mcp/applications.json
- Documentation: https://thumbgate.ai/guide
- Dashboard: https://thumbgate.ai/dashboard
- GitHub: https://github.com/IgorGanapolsky/ThumbGate
- npm: https://www.npmjs.com/package/thumbgate
- Full LLM context: https://thumbgate.ai/llm-context.md

## Compared to alternatives

- vs CLAUDE.md: ThumbGate enforces rules via hooks, not suggestions in prompts
- vs Mem0: ThumbGate is enforcement-first, not just memory storage
- vs SpecLock: ThumbGate uses adaptive Thompson Sampling, not static rules
- vs manual .cursorrules: ThumbGate auto-generates rules from feedback

## Technical stack

Node.js >=18.18, SQLite+FTS5 lesson DB, Thompson Sampling, LanceDB vectors, MCP protocol, PreToolUse hooks
