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PopNx MCPMCP servers for people who use AI · explained in plain words

Checkmcp

by H129hjversion 0.5.0i★ –iRuns on your computer
Registry nameio.github.H129hj/checkmcp

Install

Overview

Description from the maker (original English)

Audit any MCP server's security & quality — OWASP MCP Top 10 + explainable 0-100 MCP Score

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: Cybersecurity

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": {
    "checkmcp": {
      "command": "uvx",
      "args": [
        "audit-mcp",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add checkmcp -- uvx audit-mcp mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "checkmcp": {
      "command": "uvx",
      "args": [
        "audit-mcp",
        "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": {
    "checkmcp": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "audit-mcp",
        "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 H129hj, 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 Cybersecurityi

  • More stars than 0% of the other 993 servers in this category
  • Published to the registry more recently than 26% of the other 993 servers in this category
  • Basic checks equal to or better than 100% of the other 993 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 Checkmcp 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 (0.5.0) reached the registry 4 months 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: ipdata MCP by usefulapi, MaxMind minFraud MCP by usefulapi, Lambda Labs MCP by usefulapi

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

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Install

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.

CheckMCP

Vendor-neutral quality / security / context-cost audit & score for any MCP server. One uvx/pipx command → an MCP Score /100 + causal opportunities (why the score), Lighthouse-style.

Installed from PyPI as `audit-mcp` (the name checkmcp was already taken); the command is audit-mcp. Brand, site and repo remain CheckMCP / checkmcp.dev.

uvx audit-mcp https://mcp.deepwiki.com/mcp

or

pipx run audit-mcp https://mcp.context7.com/mcp --json audit-mcp https://my-mcp.example.com/mcp --token "$TOKEN"

Use it as an MCP server

audit-mcp mcp turns the auditor itself into an MCP server (stdio) exposing one tool, audit_mcp_server — so your agent can answer *"is this MCP server safe?"* mid-conversation.

# Claude Code

claude mcp add audit-mcp -- uvx audit-mcp mcp

// Cursor (.cursor/mcp.json) / Claude Desktop (claude_desktop_config.json)

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

Registry name: io.github.H129hj/checkmcp

No dependencies (stdlib only). tiktoken optional for exact token counts.

What it measures (7 pillars)

  • Security — OWASP MCP Top 10 (tool poisoning, hardcoded secrets, command injection), lethal-trifecta.
  • Tool design — sprawl/consolidation (percentile-calibrated on real servers: median ~7 tools, p95 ~42).
  • Schemas / desc — descriptions + inputSchema/outputSchema completeness.
  • Context-cost — tokens spent on tools/list, paid on every request (the #1 pain of 2026).
  • Compliance — protocol-version gap, annotations, JSON-RPC error conformance, OAuth discovery.
  • Reliability — single-shot today (not credited; continuous T3 monitoring on checkmcp.dev).
  • Coverage — the 3 primitives (tools + resources + prompts).

Hard floors: secret-in-schema → cap D, failed handshake → cap F. Every penalty is attributed: measure → mechanism → effect → Δscore.

CLI flags

flagwhat
--jsonmachine-readable report
--badgeSVG badge + README embed snippets
--htmlstandalone SEO/GEO page (JSON-LD SoftwareApplication + FAQ)
--repo owner/nameadd maintenance/license/provenance signal from GitHub
--token audit an OAuth-protected server
--min-score NCI: exit 1 if MCP Score < N
--baseline fileCI: pin tool definitions; fail on regression (rug-pull)
--gh-summaryCI: write a Markdown summary to $GITHUB_STEP_SUMMARY
--deepruntime depth via an external scanner (mcp-scan/snyk) if present
--evalsbehavioral sandbox: actually invokes read-only tools with canary inputs to catch tool-output prompt-injection, exfiltration vectors, secret/PII leakage and context bombs (sends real traffic; CI-fails on a malicious verdict)

GitHub Action

# .github/workflows/mcp-audit.yml

name: MCP audit on: [push, pull_request] jobs: checkmcp: runs-on: ubuntu-latest steps:

  • uses: actions/checkout@v4
  • uses: H129hj/checkmcp@v1 with: url: https://my-mcp.example.com/mcp min-score: "70" baseline: .checkmcp-baseline.json # commit it → fails on rug-pull

Behavioral evals (--evals)

Static analysis catches *declared* danger; --evals catches *runtime* danger by actually invoking read-only tools with canary inputs and inspecting the responses for tool-output prompt-injection, exfiltration vectors and secret/PII leakage (multilingual; optional callback-canary confirms exfil). CI-fails on a malicious verdict.

Self-hosted security gateway

Beyond auditing, CheckMCP ships an in-band MCP gateway — a proxy you put between your agent and an MCP server. It inspects every call, and in *active* mode blocks/strips tool-poisoning & exfiltration before they reach the agent. Run it in your own infra (tool traffic never leaves your network):

docker pull ghcr.io/h129hj/checkmcp-gateway:latest   # or build from source

docker run -p 8080:8080 -e GATEWAY_BACKEND_URL=https://mcp.example.com/mcp \ -e GATEWAY_MODE=active -e GATEWAY_SECRET=$(openssl rand -hex 16) \ ghcr.io/h129hj/checkmcp-gateway:latest

See [GATEWAY.md](GATEWAY.md) for config (passive/active, OAuth backends, policy, logs).

Hosted

Full reports, public directory, live badges, continuous drift monitoring, a governance policy API and a hosted gateway at [checkmcp.dev](https://checkmcp.dev).

Honest limitations

  • Percentile bands come from a growing corpus (one+ registries) — widening over time.
  • Exact tokens with pipx install "audit-mcp[exact-tokens]" (cl100k_base); otherwise chars/4 approximation.
  • Pillar weights are expert priors. python -m checkmcp.calibrate samples.json validates them against a labeled agent-success sample (per-pillar correlation + OLS-suggested weights + construct-validity R²) — supply real outcomes to close the loop.

MIT.

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