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MIT

ThumbGate MCP Server

io.github.IgorGanapolsky/thumbgate

Pre-action firewall that blocks AI agents from repeating known mistakes before tool execution.

What is the ThumbGate MCP server?

ThumbGate is a self-improving pre-action firewall for AI coding agents that intercepts tool calls at runtime via PreToolUse hooks. It evaluates proposed actions before execution to prevent costly mistakes like secret leaks, destructive commands, or broken code pushes. Lessons learned from past mistakes become local prevention rules that improve the firewall over time without retraining the model.

ThumbGate runs in the PreToolUse hook to catch dangerous tool calls before they execute. It hard-blocks detected secret leaks and process-kill commands by default, warns on high-risk patterns like `rm -rf` and force-push, and learns from operator feedback to build local prevention rules. Works with Claude Code, Cursor, Codex, Gemini CLI, and other MCP agents.

How to install ThumbGate

Copy-paste configuration for popular MCP clients.

transport: stdio
Config generated by PluginBench — verify against the source before use.
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "thumbgate": {
      "command": "npx",
      "args": [
        "-y",
        "thumbgate"
      ]
    }
  }
}

Tools & capabilities

Tools this server exposes to the agent.

  • gate_check — Read and evaluate a proposed tool call against active prevention rules and lessons
  • feedback_capture — Store accepted feedback from operator thumbs-up/thumbs-down to build local lessons
  • dashboard — View local statistics, active rules, and enforcement matrix
  • doctor — Health-check hooks, MCP wiring, and agent readiness
  • guard — Convert a past mistake into a hard prevention rule
  • rules — List active prevention rules and learned lessons
  • blocked — View gate statistics and enforcement matrix

Use cases

  • Prevent accidental deletion of critical directories or files before the agent executes `rm -rf`
  • Block secret leaks by detecting API keys and credentials in proposed tool calls before they are exposed
  • Stop force-push attempts and other destructive git operations with warnings or hard blocks
  • Learn from repeated mistakes: capture feedback on failed actions and auto-promote patterns into blocking rules
  • Enforce branch governance and scoped approval workflows for high-risk operations
  • Audit and export evidence of prevented incidents for compliance and security reviews

ThumbGate MCP server FAQ

What is ThumbGate?

ThumbGate is a pre-action firewall that intercepts AI agent tool calls before execution. It blocks detected secret leaks and process-kill commands by default, warns on high-risk patterns like `rm -rf`, and learns from operator feedback to build local prevention rules over time.

Is ThumbGate free?

Yes. Free tier includes 2 feedback captures per day (10 total) and up to 3 active auto-promoted prevention rules. Pro ($19/mo or $149/yr) offers unlimited captures, rules, personal dashboard, and DPO export. Enterprise is custom-scoped after intake.

How do I install ThumbGate in Cursor or Claude?

Run `npx thumbgate init --agent cursor` for Cursor or `npx thumbgate init --agent claude-code` for Claude Code. For any MCP agent, run `npx thumbgate serve` to start the stdio MCP server. The init command wires the PreToolUse hook automatically.

Does ThumbGate require authentication or cloud access?

No. ThumbGate is local-first and runs entirely on your machine. No cloud required for the enforcement path. Settings and lessons are stored in `~/.claude/` (machine-wide) or `./.claude/` (per-project).

How does ThumbGate learn from mistakes?

Capture feedback with `npx thumbgate capture --feedback=down` when an agent attempts something risky. Repeated patterns are auto-promoted into prevention rules that warn or block future similar attempts. Lessons stay local and improve without retraining the model.

What agents does ThumbGate work with?

ThumbGate works with Claude Code, Cursor, Codex, Gemini CLI, ForgeCode, Cline, OpenCode, Amp, and any MCP-compatible agent. Enforcement varies: hard PreToolUse blocks for Claude/Codex/Gemini, advisory MCP `gate_check` for Cursor/Cline/OpenCode.

README (reference)

Source of truth, from the repository.

ThumbGate 👍 👎

<p align="center"> <a href="https://thumbgate.ai"> <img src="docs/media/thumbgate-hero-banner.svg" alt="ThumbGate Infrastructure Firewall with Thumbs Up and Thumbs Down" width="100%" /> </a> </p> <p align="center"> <b>ThumbGate is the self-improving pre-action firewall for AI coding agents</b><br> AI coding agents repeat mistakes — and one wrong tool call can wipe a directory, leak a key, or push broken code. </p> <p align="center"> <a href="https://mcptoplist.com/server/glama%2FIgorGanapolsky%2FThumbGate"><img src="https://mcptoplist.com/badge/glama%2FIgorGanapolsky%2FThumbGate.svg" alt="MCP Toplist" /></a> <a href="https://github.com/IgorGanapolsky/ThumbGate/actions/workflows/ci.yml"><img src="https://github.com/IgorGanapolsky/ThumbGate/actions/workflows/ci.yml/badge.svg" alt="CI" /></a> <a href="https://www.npmjs.com/package/thumbgate"><img src="https://img.shields.io/npm/v/thumbgate" alt="npm version" /></a> <a href="https://www.npmjs.com/package/thumbgate"><img src="https://img.shields.io/npm/dw/thumbgate" alt="npm weekly downloads" /></a> <a href="https://github.com/IgorGanapolsky/ThumbGate"><img src="https://img.shields.io/github/stars/IgorGanapolsky/ThumbGate" alt="GitHub stars" /></a> <a href="https://github.com/marketplace/actions/thumbgate-agent-governance"><img src="https://img.shields.io/badge/GitHub_Marketplace-ThumbGate_Agent_Governance-0969da" alt="GitHub Marketplace: ThumbGate Agent Governance" /></a> <a href="LICENSE"><img src="https://img.shields.io/badge/License-MIT-green.svg" alt="License: MIT" /></a> </p> <p align="center"> <a href="#quick-start"><img src="https://img.shields.io/badge/⚡_Quick_Start-npx_thumbgate_init-22d3ee?style=for-the-badge" alt="Quick Start" /></a> <a href="https://thumbgate.ai/#demo?utm_source=github&utm_medium=readme"><img src="https://img.shields.io/badge/🎬_Watch-90s_Demo-ff647c?style=for-the-badge" alt="Watch Demo" /></a> <a href="https://thumbgate.ai/go/gpt?utm_source=github&utm_medium=readme"><img src="https://img.shields.io/badge/💬_Try-ThumbGate_GPT-56e39f?style=for-the-badge" alt="Try GPT" /></a> <a href="https://thumbgate.ai/checkout/pro?utm_source=github&utm_medium=readme"><img src="https://img.shields.io/badge/💼_Pro-$19/mo-ffd166?style=for-the-badge" alt="Pro Tier" /></a> </p>

What it does

ThumbGate is the local-first Pre-Action Checks engine for AI coding agents. It runs in the PreToolUse hook to evaluate the proposed tool call before execution — so costly mistakes can be caught before they happen.

ThumbGate GitHub star growth is measured with GitHub's privacy-safe GET /repos/{owner}/{repo}/stargazers/history endpoint (weekly counts, no stargazer identities). Run npm run stars:history -- --fixture tests/fixtures/github-star-history.json --json for the local proof. Stars are not npm installs and not revenue. The live GitHub Marketplace Action is ThumbGate Agent Governance (uses: IgorGanapolsky/ThumbGate@v1).

Usage over star count. Evaluate ThumbGate from the install path and live usage badges above (npx thumbgate init, Marketplace uses:, npm weekly downloads, GitHub clones), not from whether the repo has twenty stars or twenty thousand. No pitch deck is required. We do not farm GitHub profile badges (no YOLO-merge of protected main, no 5-minute Issue close theater, no fake Co-authored-by). Galaxy Brain needs real accepted answers in Discussions Q&A. npm run github:achievements -- --fixture tests/fixtures/github-achievements.json --json inventories what is already earned vs what we refuse to farm.

Who it's for

ThumbGate is for operators whose AI coding agents can leak a secret or destroy a checkout before a human sees the tool call (Claude Code, Cursor, Codex, Gemini CLI, MCP). Discovery should reach those operators — not a star campaign.

ThumbGate is not a GitHub star package, not fake engagement, and not a substitute for npm installs or merged PRs. Real engagement is npx thumbgate init and a PreToolUse hook that actually fires.

Tech memes (shareable)

Lightweight visuals for how agents fail without a pre-action gate:

MemeMeaning
Agent destroys prod without a gateUnchecked tool calls ship destructive commands.
Prompt vs PreToolUse hookA prompt is advice; a PreToolUse hook is enforcement.

It hard-blocks detected secret leaks and two direct self-disable command classes by default — commands that terminate the ThumbGate gate process or enable its bypass environment override. Other high-risk classes (rm -rf, force-push, fetch-and-run, direct guardrail edits) warn and log by default. Set THUMBGATE_STRICT_ENFORCEMENT=1 for strict enforcement (warnings become hard denies).

VerdictDefault behavior
⛔ Hard-blockDetected secret leaks; process-kill/environment-override self-disable
👎 Warn + logrm -rf, git push --force, fetch-and-run, direct guardrail edits — warn by default
👍 AllowEverything else

Accepted feedback is stored as local lessons. Repeated concrete failures can become prevention rules that promote from warnings to blocking gates. The firewall improves from operations without retraining the model. Prompt evaluation (npx thumbgate eval) turns accepted feedback into reusable eval cases and local proof reports.

Honest disclaimer: ThumbGate does not update model weights. It intercepts tool calls at runtime. Local-first — no cloud required for the enforcement path.

Works with Claude Code, Cursor, Codex, Gemini CLI, Amp, Cline, OpenCode, and other MCP agents.

AI Agent without ThumbGate vs Agent guarded by ThumbGate

  Agent tries:   rm -rf tests/
  ThumbGate:     👎 WARN + LOG — "Never delete test directories"
                 Pattern matched: rm.*-rf.*tests
                 Source: your thumbs-down from last Tuesday
                 Strict mode: ⛔ DENY before tool execution

Agentic development cycle fit

Agentic development is becoming a loop: Guide → Generate → Verify → Solve. ThumbGate is the pre-action gate / pre-action boundary between generated intent and executed action.


Quick Start

Want a phased walkthrough with a verify step at every stage? Follow the Progressive Setup Guide.

Progressive wiring — prove the pipe before you turn matching on. Empty dashboard is success.

npx thumbgate init          # Phase 1: hooks only
npx thumbgate doctor        # verify: exits 0 only when PreToolUse hook is wired (hidden metric = hook install, not gate count)
npx thumbgate dashboard --open  # Phase 2: open local HTML; empty stats are OK
npx thumbgate capture --feedback=down --context="Never run DROP on production tables" --what-went-wrong="agent proposed DROP" --what-to-change="require review for DROP"

Later DROP attempts in the same scope surface the check:

⚠️ Check fired: "Never run DROP on production tables"
   Pattern: DROP.*production
   Verdict: 👎 WARN + LOG   (⛔ BLOCK when THUMBGATE_STRICT_ENFORCEMENT=1)

Numbered configs: config/progressive/. Guide: progressive wiring.

MCP / Glama / registry install (stdio)

Directories and clients that install ThumbGate as an MCP server must start stdio MCP, not the HTTP API:

npx -y thumbgate serve
  • Equivalent: npx -y thumbgate mcp
  • Do not use npm start for MCP — that launches the hosted HTTP API (src/api/server.js), not the agent-facing stdio server.

▶ 90-second demo · GIF walkthrough


Install for your agent

AgentCommandEnforcement
Claude Codenpx thumbgate init --agent claude-code🛡️ Hard — PreToolUse
Codexnpx thumbgate init --agent codex🛡️ Hard — pre_tool_use
Gemini CLInpx thumbgate init --agent gemini🛡️ Hard — PreToolUse
ForgeCodenpx thumbgate init --agent forge🛡️ Hard — pre_tool_use
Cursornpx thumbgate init --agent cursor💬 Advisory — MCP gate_check
Clinenpx thumbgate init --agent cline💬 Advisory — MCP + .clinerules
OpenCodenpx thumbgate init --agent opencode💬 Advisory — MCP gate_check
Any MCP agentnpx thumbgate serve💬 Advisory — MCP gate_check
Ampnpx thumbgate init --agent amp📝 Feedback capture
GitHub Actionsuses: IgorGanapolsky/ThumbGate@v1🩺 Marketplace Action — doctor / AI inventory in CI

Per-agent guides: Claude/Codex bridge · Codex profile · Cursor · MCP setup

Install scope: machine-wide vs per-project

ScopeCommandSettingsLessonsBest for
Machine-wide (default)npx thumbgate init~/.claude/settings.json~/.claude/memory/feedback/Solo operators — same machine-local feedback store across repos
Per-projectnpx thumbgate init --project<repo>/.claude/settings.json<repo>/.claude/memory/feedback/Client / compliance — separate dashboard / isolated lessons per repo

Both scopes write mcpServers.thumbgate plus PreToolUse / UserPromptSubmit / PostToolUse / SessionStart hooks. Machine-wide is the right default for most developers. Cross-repo blocking is not automatic: a lesson learned in one project only applies elsewhere when you share the store (machine-wide) or export/import lessons.

MCP tools (surface): gate_check (read/evaluate proposed tool call), feedback capture + session tools (write), dashboard/stats (read). Destructive agent actions stay blocked/warned by PreToolUse — ThumbGate does not execute user shell commands for you.


Discoverable slash-commands — the guardrail layer for spec-driven agents

Spec-driven agent frameworks like GSD (get-shit-done) and GitHub Spec Kit plan and generate work. ThumbGate is the guardrail layer for spec-driven agents: it sits after the plan, on the boundary between a generated tool call and its execution — alongside GSD / Spec-Kit, not instead of them.

npx thumbgate init installs these into your agent palette:

CommandWhat it does
/thumbgate-dashboardOpen local project dashboard
/thumbgate-guardTurn last mistake into a hard prevention rule
/thumbgate-rulesList active rules & lessons
/thumbgate-blockedGate stats + enforcement matrix
/thumbgate-protectBranch governance + scoped approval
/thumbgate-doctorHealth-check hooks, MCP, readiness

Pricing & buyer paths

Free tier: 2 feedback captures/day (10 total) and up to 3 active auto-promoted prevention rules. Pro ($19/mo or $149/yr) is the individual tier for unlimited rules, history-aware lessons, linked feedback session flow, personal dashboard, and DPO export. Enterprise is custom and scoped after intake; hosted team lesson sync and a hosted org dashboard are not general availability.

FreePro ($19/mo or $149/yr)Enterprise
Local CLI + PreToolUse✅✅Scoped after intake
Feedback captures2 feedback captures/day (10 total)UnlimitedScoped after intake
Active auto-promoted rulesup to 3 active auto-promoted prevention rulesUnlimitedScoped after intake
Personal dashboard + DPO export—✅Reviewed during intake
Hosted team lesson sync——Not general availability
Hosted org dashboard——Not general availability

Enterprise intake path: the Workflow Hardening Sprint scopes one repeated failure before any broader rollout commitment. Start intake →

Local technical path: install the CLI and use init plus the documented setup so Pre-Action Checks evaluate tool calls where the agent actually runs.

First-dollar activation path: open the ThumbGate GPT, paste the risky action, capture typed feedback (thumbs down: / thumbs up:). Native ChatGPT rating buttons are not the ThumbGate capture path. Ask: what repeated AI mistake would be worth catching before the tool executes?

Paid path for individual operators: ThumbGate Pro is the self-serve side lane for a personal dashboard and export-ready evidence.

Start free · Pro $19/mo · Live Dashboard · Team Sprint intake · Workflow Hardening Sprint · First Dollar Playbook

Popular buyer questions: AI search topical presence · Relational knowledge and AI recommendations · AI Mode ads for agent governance · MCP tool governance · AI agent pre-action approval gates · Background agent governance · GPT-5.5 model evaluation · Stop repeated AI agent mistakes · Browser automation safety · Native messaging host security · Autoresearch agent safety · Cursor guardrails · Codex CLI guardrails · Gemini CLI memory + enforcement · Google Cloud MCP guardrails · Roo Code alternative: migrate to Cline


How it works (short)

  1. Capture 👍/👎 feedback (CLI, MCP, linked feedback session flow / open_feedback_session, or ThumbGate GPT)
  2. Promote concrete lessons via history-aware lesson distillation into prevention rules
  3. Evaluate the next proposed tool call against active rules (literal/AST + local vectors)
  4. Allow / warn / deny before the tool runs
npx thumbgate brain --write   # → .thumbgate/BRAIN.md (lessons + gates in one artifact)

Pro operators can invoke search_lessons through MCP and use npx thumbgate lessons from the CLI. History-aware feedback sessions and lesson search are Pro capabilities; Free does not include recall or search.

<details> <summary><b>Architecture diagram & stack</b></summary>

ThumbGate Architecture

flowchart LR
    A["Agent tool call"] --> B{"Rule match?"}
    B -- exact --> D["On-device gate"]
    B -- semantic --> C["Local LanceDB"]
    C --> D
    D -- secret/kill --> E["⛔ Hard-block"]
    D -- known-bad --> G["👎 Warn + log"]
    D -- safe --> F["👍 Allow"]
</details> <details> <summary><b>Built-in checks</b></summary>
⛔ secret-exfiltration → hard-block (default)
⛔ self-protect-kill   → hard-block (default)
⛔ self-protect-env    → hard-block (default)
⚠️ force-push          → warn; hard-block under strict
⚠️ protected-branch    → warn; hard-block under strict
⚠️ unresolved-threads  → warn; hard-block under strict
⚠️ package-lock-reset  → warn; hard-block under strict
</details> <details> <summary><b>CLI cheatsheet</b></summary>
npx thumbgate init
npx thumbgate doctor
npx thumbgate capture up|down "<text>"
npx thumbgate lessons
npx thumbgate brain --write
npx thumbgate dashboard --open
npx thumbgate break-glass --reason="ThumbGate over-fired"   # 5-min recovery
</details> <details> <summary><b>Pro: lesson + DPO export</b></summary>
# Portable lessons
curl -X POST http://localhost:3456/v1/lessons/export \
  -H "Authorization: Bearer $THUMBGATE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"outputPath": "./lessons-export.json"}'

# DPO pairs for fine-tuning
curl -X POST http://localhost:3456/v1/dpo/export \
  -H "Authorization: Bearer $THUMBGATE_API_KEY" \
  -o dpo-pairs.jsonl
</details>

Tech Stack

LayerTech
RuntimeNode.js ≥18
InterfacesMCP stdio, HTTP API, CLI
StorageSQLite + FTS5, LanceDB vectors, JSONL logs
IntelligenceMemAlign dual recall, Thompson Sampling, local embeddings
Billing / hostStripe, Railway
ExecutionRailway, Cloudflare Workers, Docker Sandboxes
GovernanceWorkflow Sentinel, control plane, Docker Sandboxes

Every Changeset is tied to the exact main merge commit and generates Verification Evidence for Release Confidence.


Integrations (compact)

SurfaceStart here
Open ThumbGate GPTthumbgate.ai/go/gpt — ThumbGate GPT: start here. Paste agent actions, get advice + checkpointing. No, users do not have to keep chatting inside the ThumbGate GPT to use ThumbGate — the hard enforcement layer still runs where the work happens.
Install Codex PluginOpen the Codex plugin install page: thumbgate.ai/codex-plugin · zip: thumbgate-codex-plugin.zip · plugins/codex-profile/INSTALL.md
Claude Desktop .mcpblatest release
VS Code / Open VSXplugins/vscode-extension/README.md
Antigravity-compatibleplugins/antigravity-extension/INSTALL.md
JetBrainsplugins/jetbrains-plugin/README.md · JetBrains Marketplace path for the same runtime
ChatGPT App / GPT Actionthumbgate.ai/chatgpt-app
ThumbGate-Core (staging)https://github.com/IgorGanapolsky/ThumbGate-Core — pre-release staging + a few internal cache scripts; not the product moat

Docs

Full index: docs/INDEX.md

NeedLink
Agent workflow contractWORKFLOW.md
Ready-for-agent intake.github/ISSUE_TEMPLATE/ready-for-agent.yml
Verification Evidencedocs/VERIFICATION_EVIDENCE.md
Release Confidencedocs/RELEASE_CONFIDENCE.md
Changeset strategydocs/CHANGESET_STRATEGY.md
First Dollar Playbookdocs/FIRST_DOLLAR_PLAYBOOK.md
Security policySECURITY.md
Threat modelTHREAT_MODEL.md
Federal / regulateddocs/FEDERAL.md
Commercial Truthdocs/COMMERCIAL_TRUTH.md
Issues / PRsGitHub Issues · PR template

FAQ (one-liners): Not a fine-tuner (runtime intercept only). Different from CLAUDE.md / .cursorrules (those are context; ThumbGate is an external allow/warn/deny before tools run).


Who builds this

Igor Ganapolsky — payments (Stripe/Connect), AI agent guardrails/MCP, Android + backends. Small number of contract slots: $120–150/hr, 1099, remote US. LinkedIn · thumbgate.ai

License

MIT — see LICENSE. Project policy: SECURITY.md · THREAT_MODEL.md.

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