ipdata MCP by usefulapi
Look up location, network, company and threat data for IP addresses and ASNs in ipdata.
Description from the maker (original English)
Audit any MCP server's security & quality — OWASP MCP Top 10 + explainable 0-100 MCP Score
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": {
"checkmcp": {
"command": "uvx",
"args": [
"audit-mcp",
"mcp"
]
}
}
}Run this in your terminal
claude mcp add checkmcp -- uvx audit-mcp mcpPaste 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.
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.
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 7, 2026
The registry name was verified with the GitHub account H129hj, 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 (0.5.0) reached the registry 4 months ago.
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: ipdata MCP by usefulapi, MaxMind minFraud MCP by usefulapi, Lambda Labs MCP by usefulapi
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
Look up location, network, company and threat data for IP addresses and ASNs in ipdata.
MCP server for MaxMind minFraud — score transactions for fraud risk from your AI assistant.
Read GPU instances, types, images, filesystems and firewall rules; launch and terminate instances.
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.
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
checkmcpwas already taken); the command isaudit-mcp. Brand, site and repo remain CheckMCP / checkmcp.dev.
uvx audit-mcp https://mcp.deepwiki.com/mcp
pipx run audit-mcp https://mcp.context7.com/mcp --json audit-mcp https://my-mcp.example.com/mcp --token "$TOKEN"
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.
inputSchema/outputSchema completeness.tools/list, paid on every request (the #1 pain of 2026).Hard floors: secret-in-schema → cap D, failed handshake → cap F. Every penalty is attributed: measure → mechanism → effect → Δscore.
| flag | what |
|---|---|
--json | machine-readable report |
--badge | SVG badge + README embed snippets |
--html | standalone SEO/GEO page (JSON-LD SoftwareApplication + FAQ) |
--repo owner/name | add maintenance/license/provenance signal from GitHub |
--token | audit an OAuth-protected server |
--min-score N | CI: exit 1 if MCP Score < N |
--baseline file | CI: pin tool definitions; fail on regression (rug-pull) |
--gh-summary | CI: write a Markdown summary to $GITHUB_STEP_SUMMARY |
--deep | runtime depth via an external scanner (mcp-scan/snyk) if present |
--evals | behavioral sandbox: actually invokes read-only tools with canary inputs to catch tool-output prompt-injection, exfiltration vectors, secret/PII leakage and context bombs (sends real traffic; CI-fails on a malicious verdict) |
# .github/workflows/mcp-audit.yml
name: MCP audit on: [push, pull_request] jobs: checkmcp: runs-on: ubuntu-latest steps:
--evals)Static analysis catches *declared* danger; --evals catches *runtime* danger by actually invoking read-only tools with canary inputs and inspecting the responses for tool-output prompt-injection, exfiltration vectors and secret/PII leakage (multilingual; optional callback-canary confirms exfil). CI-fails on a malicious verdict.
Beyond auditing, CheckMCP ships an in-band MCP gateway — a proxy you put between your agent and an MCP server. It inspects every call, and in *active* mode blocks/strips tool-poisoning & exfiltration before they reach the agent. Run it in your own infra (tool traffic never leaves your network):
docker pull ghcr.io/h129hj/checkmcp-gateway:latest # or build from source
docker run -p 8080:8080 -e GATEWAY_BACKEND_URL=https://mcp.example.com/mcp \ -e GATEWAY_MODE=active -e GATEWAY_SECRET=$(openssl rand -hex 16) \ ghcr.io/h129hj/checkmcp-gateway:latest
See [GATEWAY.md](GATEWAY.md) for config (passive/active, OAuth backends, policy, logs).
Full reports, public directory, live badges, continuous drift monitoring, a governance policy API and a hosted gateway at [checkmcp.dev](https://checkmcp.dev).
pipx install "audit-mcp[exact-tokens]" (cl100k_base); otherwise chars/4 approximation.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.