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mcpgawk

by gawk-devversion 0.1.83i★ –iRuns on your computer
Registry nameio.github.gawk-dev/mcpgawk

Install

Overview

Description from the maker (original English)

Measure MCP servers, pin the approved tool surface, refuse calls to tools that changed. Local-first.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "mcpgawk": {
      "command": "uvx",
      "args": [
        "mcpgawk",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add mcpgawk -- uvx mcpgawk mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "mcpgawk": {
      "command": "uvx",
      "args": [
        "mcpgawk",
        "mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "mcpgawk": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "mcpgawk",
        "mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account gawk-dev, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32572 servers in this category
  • Published to the registry more recently than 93% of the other 32572 servers in this category
  • Basic checks equal to or better than 100% of the other 32572 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is mcpgawk safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.83) reached the registry 2 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, AvaHR

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Spec Driven Development

by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated yesterday
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AvaHR

by avahr.com

Read hiring data and create inactive assessment and questionnaire drafts for human review.

Runs in the cloudUpdated today
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

One gateway in the path. On your machine.

Featured on Product Hunt.

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 on this same install fetches the paid engine and turns those on — one more command, nothing else to set up.

Watch: mcpgawk in 64 seconds. A tool you approved changes in an update; mcpgawk refuses the call until you decide.

mcpgawk demo — its own output, in a sandbox that touches nothing of yours. Run the same command and you get the same thing.

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 guard installs 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 verify drives 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 install puts 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 verify drives 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 decide opens 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 changes shows 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-remote bridge).
  • 💸 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-chain and --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 # 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: (or keychain: @ ) 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 (--verbose for the full per-tool table).
  • Integrity pin — a hash that changes if the server silently rewrites its tools; --track turns 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 actual

Only the beginning is shown; read the rest in the repo

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