Model Context Protocol サーバーにおける、不正なツールの変更を監視、検証、およびブロックするためのローカルゲートウェイを提供します。
別名 gawk-dev/mcpgawk
- スター
- 1
- ツール
- —
- ダウンロード数(30日間)
- 4,015
- 最新バージョン
- 0.1.87
- 最終コミット
- 2026年11月10日
- ライセンス
- Apache-2.0
mcpgawk MCPとは
mcpgawkはMCPサーバーです。 Model Context Protocol サーバーにおける、不正なツールの変更を監視、検証、およびブロックするためのローカルゲートウェイを提供します。.
プロジェクトのREADMEから生成された概要
mcpgawk MCP server について
mcpgawk は、Model Context Protocol サーバーを使用する開発者のためのローカルセキュリティゲートウェイとして機能します。これは、サーバーが初回承認後にツールの定義を変更し、エージェントが意図せず新しい未承認の関数を実行してしまうリスクに対処します。本ソフトウェアは完全にお使いのマシン上で動作し、データをアップロードしないため、インベントリや決定事項のプライバシーが確保されます。
ユーザーは、コマンドラインインターフェース、または VS Code や Cursor 用の専用拡張機能を通じてシステムを操作できます。ツールセットには、実行前フックをインストールする mcpgawk guard、サンドボックス内でツールをテストする mcpgawk verify、時間の経過に伴うツールサーフェスの差異を表示する mcpgawk changes などのコマンドが含まれます。stdio、SSE、HTTP を含むさまざまなトランスポートをサポートしています。より広範な監視を必要とするチーム向けに、mcpgawk Platform では、サブスクリプションモデルを通じて mcpgawk enforce や mcpgawk monitor といったエンタープライズ機能を提供しています。
できること
- 1サーバーの動作を隔離環境で監査サーバーをサンドボックス内で実行し、信頼する前にデータの持ち出しや SSRF などの悪意のある活動を検出できます。
- 2コンテキストウィンドウのコストを監視開発者は、エージェントのパフォーマンスと効率を管理するために、どのツールが最も多くのトークンを消費しているかを特定できます。
- 3サイレントなツール更新の検出追跡機能を使用して、サーバーがツールの説明や入力スキーマを書き換えたタイミングを特定できます。
プロジェクトの README から作成されています。すべてのユースケースは、その引用と照らし合わせて確認されています。
mcpgawk MCPのインストール方法
フォーマット検証日 2026年11月10日Cursor に追加Gooseに追加Claude Codeにmcpgawk MCPをインストール
$ claude mcp add mcpgawk -- uvx mcpgawkCursorにmcpgawk MCPをインストール
~/.cursor/mcp.json
{
"mcpServers": {
"mcpgawk": {
"command": "uvx",
"args": [
"mcpgawk"
]
}
}
}VS Codeにmcpgawk MCPをインストール
.vscode/mcp.json
{
"servers": {
"mcpgawk": {
"type": "stdio",
"command": "uvx",
"args": [
"mcpgawk"
]
}
}
}VS Code CLIにmcpgawk MCPをインストール
$ code --add-mcp '{"name":"mcpgawk","type":"stdio","command":"uvx","args":["mcpgawk"]}'Claude Desktopにmcpgawk MCPをインストール
claude_desktop_config.json
{
"mcpServers": {
"mcpgawk": {
"command": "uvx",
"args": [
"mcpgawk"
]
}
}
}Codexにmcpgawk MCPをインストール
$ codex mcp add mcpgawk -- uvx mcpgawkCodex config.tomlにmcpgawk MCPをインストール
~/.codex/config.toml
[mcp_servers.mcpgawk] command = "uvx" args = ["mcpgawk"]
Gemini CLIにmcpgawk MCPをインストール
$ gemini mcp add -s user mcpgawk uvx -- mcpgawkGemini settings.jsonにmcpgawk MCPをインストール
~/.gemini/settings.json
{
"mcpServers": {
"mcpgawk": {
"command": "uvx",
"args": [
"mcpgawk"
]
}
}
}設定
GITHUB_PERSONAL_ACCESS_TOKEN
| 名前 | 説明 | 種類 |
|---|---|---|
| GITHUB_PERSONAL_ACCESS_TOKEN | — |
自動チェック
実行日 2026年11月14日完全なレポート →自動チェックに合格しました。これはセキュリティ監査ではありません。コードを読み、サーバーに必要最小限のアクセス権を与えてください。 チェックの仕組み
- ソースリポジトリがリンクされており、アクセス可能gawk-dev/mcpgawk is public and reachablegithub.com/gawk-dev/mcpgawk ↗合格
- パッケージがこのリポジトリをソースとして指定mcpgawk names gawk-dev/mcpgawk as sourcepypi.org/project/mcpgawk/ ↗合格
- ビルドの来歴 (Sigstore 証明)Sigstore attestation for mcpgawkpypi.org/project/mcpgawk/ ↗合格
- オープンソースライセンス (OSI)Apache-2.0spdx.org/licenses/Apache-2.0.html ↗合格
- 過去1年以内にコミットまたはリリースありLast commit or release 2026-11-10github.com/gawk-dev/mcpgawk ↗合格
- OpenSSF Scorecard未チェック
- パッケージ名が有名なパッケージに酷似していないNo popular package one edit away from mcpgawk合格
- パッケージおよびその依存関係に重大な勧告なし38 resolved dependencies checked; no critical advisoryosv.dev ↗合格
- モデルへの隠れた指示がない0 tool descriptions and the README read; no override phrases, credential paths or hidden characters合格
- 破壊的なツールがラベル付けされている未チェック
- リモートエンドポイントが MCP ハンドシェイクに応答未チェック
README
GitHubで見るmcpgawk
Your agents call Model Context Protocol servers that can change what their tools do after you approved them, and the agent will call the new one without noticing. mcpgawk reads every server your agents can reach, checks every call against a baseline you approved, and blocks the ones that changed. It runs on your machine and uploads nothing.
The same engine powers mcpgawk Platform: mcpgawk enforce puts one endpoint in front of the
whole fleet with a key per caller, policy on every call and a hash-chained audit log, and
mcpgawk monitor watches the servers you approved around the clock and tells you when one drifts.
This free layer is the seeing and the blocking underneath it. mcpgawk Platform is one subscription
per person for up to 3 machines: start a free 7-day trial at https://mcp.gawk.dev/trial.html?utm_source=github&utm_medium=readme
(no card) or subscribe at https://mcp.gawk.dev/subscribe. Then mcpgawk login <key> on this same
install fetches the paid engine and turns those on — one more command, nothing else to set up.
Why
A server you approved can change what its tools do afterwards. Nothing in MCP tells your agent that happened — it just calls the new tool. That is the rug-pull, and it is the case mcpgawk is built for.
Two things follow from being able to see a server properly. You find out what each one can reach before you trust it, and you find out what it costs: every tool is loaded into your context on every request, used or not.
How it's different
- It blocks, it does not only report. A scanner tells you afterwards.
mcpgawk guardinstalls one pre-execution hook and a tool that appeared after you approved the server does not run. - It runs the server, not just reads it.
mcpgawk verifydrives tools in a sandbox and reports what they actually did — exfiltration, SSRF, poisoning — reproduced before it is reported. - Nothing is uploaded. Cloud scanners send your inventory to a server and gate the verdict there. Every decision here is made on your machine, with no account and nothing to sign in to.
- It says what it did not check. Skipped tools are named as skipped, never counted as clean.
Features
- 🛑 Block a changed tool before it runs —
mcpgawk guard installputs one pre-execution hook in your agent's loop. The decision is local, in about 10ms, with nothing to sign in to. Works on 6 of the 21 supported clients; the rest have no hook point and are named, not glossed over. - 🧪 Run it, don't just read it —
mcpgawk verifydrives tools in a sandbox and reports what they did: exfiltration, SSRF, tool poisoning, secret leaks. The sandbox is a proxy by default, so it needs no Docker; Docker adds full container isolation when you have it. Safe mode drives only provably read-only tools, and every tool it skips is named as skipped. - 🧑⚖️ Approval needs a person —
mcpgawk decideopens a local screen for what changed. The buttons live on the tokened link printed in your terminal, so an agent that opened the page cannot approve its own way past a block. - 🖥️ One local panel —
mcpgawk panel: every server, every decision, every piece of evidence. - 📜 The changelog no vendor publishes —
mcpgawk changesshows every change to a server's tool surface between the snapshots you have recorded: tools added or removed, input schemas widened, descriptions and annotations rewritten. It reads your local history, so it works for a server you approved weeks ago — the one thing a fresh scan can never tell you. - 🔌 Any transport — stdio, streamable-HTTP, SSE, and OAuth remotes (via the
mcp-remotebridge). - 💸 Token cost index — exactly what each tool adds to your context at connect, plus the 3 heaviest tools.
- 🧾 Capability facts — write / exfil-capable / declared annotations, straight from the schema, plus a trust-surface summary (% write, % exfil-capable, destructive-declared count) and an annotation-completeness score.
- 📌 Integrity pin + drift — catch a server that silently rewrites its tools (
--track). - 🚩 Bounded signals — injection-shaped descriptions, cross-server shadowing, under-declaring Server Cards — pointers for a human, never verdicts.
- 🔒 Zero egress, by construction — the measurement layers import no network library. Enforced by a test.
Two checks are opt-in and make an explicit exception (see Guarantees):
--supply-chainand--oauth-scopes.
Get it — three ways
CLI (any terminal):
uv tool install --force mcpgawk # or: pipx install --force mcpgawk
mcpgawk # finds every agent config on the machine itself
Run it as an MCP server: mcpgawk mcp (stdio), or uvx mcpgawk mcp.
Editor (VS Code / Cursor): install mcpgawk from the VS Code Marketplace or Open VSX. It scans your workspace mcp.json and shows cost + capability flags inline. The extension drives this engine as a subprocess — it is built and released separately, so its source is not in this repository.
CI (GitHub Action): gate every PR on token budget / drift (Marketplace):
- uses: gawk-dev/mcpgawk@v1
with: { config: mcp.json, max-tokens: 8000, fail-on-flagged: true }
When to run it
- Once, then leave it on —
mcpgawk guard install. After that a tool that appears on a server you already approved does not get called. - Before you add a server — see what it costs and what it can do, before you trust it.
- When your agent feels slow or picks the wrong tool — it's often MCP bloat (too many / too-heavy tools).
- On every PR — the CI gate catches drift and creeping token cost.
- If you publish an MCP server — see what it costs your users and how it reads to a client, and fix it (usually one line per tool). Lean + well-annotated is a differentiator.
Use
mcpgawk # first run: every agent config on this machine
mcpgawk demo # the whole arc in a sandbox — approve, drift, block
mcpgawk guard install # put the baseline in your agent's loop
mcpgawk guard status # is protection actually on?
mcpgawk decide # what changed, and approve it as a human
mcpgawk panel # the local page: servers, decisions, evidence
mcpgawk verify mcp.json # run the servers and watch what they do
mcpgawk changes # what changed on your servers since you approved them
mcpgawk login <key> # licence? one command fetches the paid engine (enforce, monitor)
Scanning on its own, if that is all you want:
mcpgawk scan mcp.json # a whole config
mcpgawk scan --stdio "npx -y @modelcontextprotocol/server-filesystem@2026.8.31 /tmp"
mcpgawk scan --http https://host/mcp --header "Authorization: Bearer $TOKEN"
mcpgawk scan --sse https://host/sse
mcpgawk scan mcp.json --track # record + detect rug-pulls over time
mcpgawk scan mcp.json --json # machine-readable labels
mcpgawk scan mcp.json --verbose # full per-tool table, not just flagged tools
mcpgawk scan mcp.json --supply-chain # opt-in: npm/PyPI deprecation check (network)
mcpgawk scan mcp.json --oauth-scopes # opt-in: decode a supplied Bearer JWT's scope
Keep tokens out of the config file. Under mcpgawk wrap, an env value written as keychain:<service>
(or keychain:<service>@<account>) is read from your macOS Keychain when the server starts and placed
in the server's environment only. The config holds a reference, the agent sees a reference, mcpgawk
stores nothing. A reference that cannot be read refuses to start the server and names the reference,
never a value.
"github": { "command": "mcpgawk", "args": ["wrap", "--", "npx", "-y", "@modelcontextprotocol/server-github"],
"env": { "GITHUB_PERSONAL_ACCESS_TOKEN": "keychain:gh-work" } }
What it reports
- Cost index — tokens each tool adds at connect (named tokenizer; a comparable index, not an absolute Claude count), plus the 3 heaviest tools.
- Trust surface — capability facts (write/mutating, exfil-capable, declared annotations) rolled up into % write, % exfil-capable, and a destructive-declared count.
- Annotation completeness — a transparent composite (annotated ÷ total tools declaring read/write intent), not a risk score.
- Coverage — tools, prompts, and resources counted (
--verbosefor the full per-tool table). - Integrity pin — a hash that changes if the server silently rewrites its tools;
--trackturns it into rug-pull detection over time. - Bounded signals — precise, low-false-positive pointers for a human to review, never verdicts: injection-shaped descriptions (tools and prompts), cross-server name shadowing, and public Server Cards that under-declare what the server actually exposes.
- Supply-chain (opt-in,
--supply-chain) — checks the launched package against the public npm/PyPI registry for deprecation/yank status. - OAuth scopes (opt-in,
--oauth-scopes) — locally decodes a supplied Bearer JWT'sscopeclaim.
Guarantees
- No inventory egress. The only network is the protocol client talking to the server you point
it at. The measurement layers import no network library — they cannot egress by construction
(enforced by a test). Public Server Card discovery is fetched with no auth and no redirect-following.
Two flags are the explicit, opt-in exception:
--supply-chainsends the launched package's name (and pinned version, if any) — never your tool inventory — to the public npm registry or PyPI JSON API.--oauth-scopesmakes no network call at all; it locally decodes a Bearer JWT you already supplied. Neither runs unless you pass the flag. - Facts ≠ heuristics. Exact capability facts and the token index never mix with the bounded heuristic signals — separate in code, separate in output.
- Reproducible. One command, identical numbers.
- Tracks the protocol. Built on the official
mcpSDK, which negotiates the protocol version.
Develop
uv run --extra dev --with mcp --with tiktoken --with httpx python -m pytest -q
CI gate — GitHub Action
Scan your MCP servers on every pull request and fail the build if one gets too heavy or trips a signal. It runs entirely in your runner — nothing is uploaded — and posts a per-server cost/flag table to the job summary.
- uses: gawk-dev/mcpgawk@v1
with:
config: mcp.json # or: stdio / http / sse — a single server
max-tokens: 8000 # fail if any server loads more than this at connect
fail-on-flagged: true # fail if any bounded signal fires
Available on the GitHub Marketplace.
Contributing
Issues and PRs welcome. Please read CONTRIBUTING.md first, and see the design boundaries in THREAT-MODEL.md. Security reports go through SECURITY.md (privately, not a public issue).
License
Apache-2.0 — see LICENSE. Part of the nativerse · gawk.dev family. Site and docs: mcp.gawk.dev. The value is in the repo, not a cloud.
Use it from your agent (skill)
Let your coding agent run the checks itself — whenever it adds, upgrades or audits an MCP server:
# Claude Code: install the plugin (the skill, nothing else)
/plugin install mcpgawk --marketplace gawk-dev/mcpgawk
# Any other agent: copy the skill folder into its skills directory
mkdir -p ~/.claude/skills && cp -r plugin/skills/mcpgawk ~/.claude/skills/mcpgawk
The skill teaches the agent to measure a server BEFORE trusting it, audit an MCP-2 upgrade as a baseline diff instead of blind re-trust, and relay every consent prompt to you verbatim.
mcpgawk MCPのよくある質問
mcpgawk MCPをClaude Codeに追加するには
ターミナルでclaude mcp add mcpgawk -- uvx mcpgawkを実行します。すべてのプロジェクトで利用するには--scope userを追加します。
mcpgawk MCPをCursorに追加するには
~/.cursor/mcp.jsonを開き、上記のインストールセクションに示すCursor設定を使ってmcpServersの下にサーバーを追加します。
mcpgawk はデータをクラウドにアップロードしますか?
いいえ、ローカルファーストのツールであり、お使いのマシン上で動作し、データは一切アップロードしません。
mcpgawk はツールの変更をどのように処理しますか?
すべてのサーバーを読み込み、呼び出し内容を承認済みのベースラインと照合し、変更されたツールをブロックします。
セキュリティ脆弱性のテストに使用できますか?
はい、verify コマンドを使用してサンドボックス内でツールを実行し、データの持ち出し、SSRF、およびツールポイズニングに関するレポートを作成できます。
スキャン中にツールがスキップされた場合はどうなりますか?
スキップされたツールは、安全であるとみなされるのではなく、明示的にスキップされたものとして記録されます。
