Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Measure MCP servers, pin the approved tool surface, refuse calls to tools that changed. Local-first.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
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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 mcpPaste 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.
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.
Runs on your computer; the tool list appears in your AI app after you install it.
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 6, 2026
The registry name was verified with the GitHub account gawk-dev, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
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.
The registry does not list a required key, though some servers ask you to sign in on first use.
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).
The GitHub repo last changed –, and the latest version (0.1.83) reached the registry yesterday.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, Dechonet MCP
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
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
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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.
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.
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.
mcpgawk guard installs one pre-execution hook and a tool that appeared after you approved the server does not run.mcpgawk verify drives tools in a sandbox and reports what they actually did — exfiltration, SSRF, poisoning — reproduced before it is reported.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.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.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.mcpgawk panel: every server, every decision, every piece of evidence.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.mcp-remote bridge).--track).--supply-chain and --oauth-scopes.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 }
mcpgawk guard install. After that a tool that appears on a server you already approved does not get called.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" } }
--verbose for the full per-tool table).--track turns it into rug-pull detection over time.Only the beginning is shown; read the rest in the repo