Automation Auditor MCP

Name: Automation Auditor MCP
Author: ahamdjin

by ahamdjinversion 0.1.0i★ 0iRuns on your computer

Registry nameio.github.ahamdjin/automation-auditor-mcp

Install

Overview

Description from the maker (original English)

Inspect n8n, Dify, Trigger.dev and Activepieces automation exports before deployment.

PopNx MCP’s three pillars

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

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi2 of 2 passedChecked from public information; code not scanned yet
UsageiVery new↓ 26/wk · ★ 0

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: Developer tools

Install

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

Before you install

Basic checks: 2 of 2 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?

ClaudeClaude CodeCursorVS CodeChatGPT

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": {
    "automation-auditor": {
      "command": "uvx",
      "args": [
        "automation-auditor-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add automation-auditor -- uvx automation-auditor-mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "automation-auditor": {
      "command": "uvx",
      "args": [
        "automation-auditor-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": {
    "automation-auditor": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "automation-auditor-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 10, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account ahamdjin, which owns the repo
✓ Pass
Still maintained
Code last changed 20 days ago
… 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 Developer toolsi

More stars than 0% of the other 5720 servers in this category
Published to the registry more recently than 58% of the other 5720 servers in this category
Basic checks equal to or better than 100% of the other 5720 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 Automation Auditor MCP safe?

It passed 2 of 2 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 20 days ago, and the latest version (0.1.0) reached the registry 21 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: REA, Netdata, Front-End Checklist

Alternatives

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

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Front-End Checklist

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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.

Automation Auditor MCP

One MCP server, several real automation export formats. Built and maintained by Ahmad Yar.

This is an early-stage implementation. See the PyPI package and MCP Registry entry for current publishing and version details. Host compatibility and real-client MCP behavior should be verified before production use. It performs read-only static checks on supplied text; it never reads your repo on its own, contacts automation accounts, runs JS, or connects to API endpoints.

Supported inputs and honest limitations

Platform	Input	Checks	Boundary
n8n	Exported workflow JSON	Missing/duplicate node names or IDs, broken connections, missing webhook paths	Static structure; no credential or live execution checks
Dify	Exported workflow DSL YAML/JSON	Missing or duplicate node IDs, broken edges, start/end checks	YAML DSL varies with releases; no runtime/model validation
Trigger.dev	Source of task definitions (TypeScript/JS)	Literal task IDs, duplicates, advisory duration notes	Heuristics only; run TypeScript and Trigger.dev build/tests
Activepieces	Flow JSON or flow version object	Trigger presence, duplicate step names, invalid-marked steps	Common nextAction/branches only; not an exhaustive flow validator
OpenAPI	JSON spec	Existing GPT Tools integration checker	Best effort, not complete OpenAPI schema validation
URL preflight	HTTPS URL	Known unsafe URL schemes/addresses using GPT Tools	No DNS or fetch. "manual_review" is not "safe."

"Any automation platform" is not possible without an adapter for its native format. Unsupported platforms are reported as unsupported, rather than passing a meaningless check. You can add adapters to the registry in core.py and corresponding tests. Make, Zapier and Pipedream are not advertised as supported in v0.1.

Install

Install with Python 3.11+:

pip install automation-auditor-mcp

Configure a compatible MCP client:

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

uvx requires uv. Confirm the package's current published version on PyPI and test the configuration with your MCP host before production use.

For development from source:

python -m pip install -e . python -m unittest discover -s tests -v automation-audit examples/n8n-valid.json --platform n8n automation-auditor-mcp

The last command runs the MCP stdio server and waits for a connected client. Use a host or MCP Inspector to communicate with it; starting from an ordinary terminal should not print output.

MCP tool API

audit_workflow(platform, source): Pass the full text contents of an export or Trigger.dev source file. platform is auto, n8n, dify, trigger, trigger.dev, or activepieces. Max 250,000 characters. The server does not read files by path.
audit_openapi(spec_json): JSON OpenAPI document; uses the existing ahmad-yar-gpt-tools library.
preflight_url(url): Pure URL screening; never performs DNS lookup or HTTP request. A permitted syntax becomes manual_review because real fetching requires request-time controls.
list_supported_platforms(): Exact supported formats and known limitations.

Findings include a stable rule ID, severity, location, brief message, recommendation and confidence. They intentionally do not echo node names, raw URLs, credentials or source snippets. A report of no_findings_detected is not proof of safety.

Example: detect a broken n8n connection

The MCP client passes exported workflow JSON to audit_workflow("n8n", source). If a connection points to a deleted node, the structured report includes rule N8N009 with severity error. The assistant can explain the error and request the user to fix it. This tool never edits workflow files itself.

Tests

python -m unittest discover -s tests -v

Test fixtures use only fictional metadata; no API keys or customer information. The core format inspectors require no network and do not import MCP at test time; MCP SDK integration requires installing dependencies.

Release and registry maintenance checklist

Keep the public source repository and installation instructions synchronized with released artifacts.
Run all tests and verify MCP Inspector calls in a real MCP client for each release. Improve Trigger.dev analysis with a TypeScript AST parser before describing it as comprehensive.
For each release, verify the published version and metadata on PyPI, including its source and homepage links.
Preserve the README marker mcp-name: io.github.ahamdjin/automation-auditor-mcp inside the PyPI long description for Registry package ownership verification.
When releasing a new version, validate server.json using the official MCP Registry publisher, and keep its PyPI identifier, version and stdio transport accurate.
Verify Registry metadata after each release using the official Registry API. The Registry hosts metadata, not the package itself.

The Registry's official publishing requirements explain PyPI ownership verification.

Security, licensing and attribution

No source content is intentionally stored, sent externally, executed, or used for model inference. The MCP host may log inputs or reports separately. YAML aliases are refused, duplicate JSON/YAML fields are rejected, and input size is bounded. Trigger.dev regex checks have low confidence; a source audit cannot guarantee runtime behavior. Never treat URL preflight as SSRF prevention.

License: Apache-2.0. Upstream ahmad-yar-gpt-tools also uses Apache-2.0.

Source (after repository creation): https://github.com/ahamdjin/automation-auditor-mcp Creator: https://www.ahmadyar.co/

Automation Auditor MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Developer toolsi

Common questions

Alternatives

REA

Netdata

Front-End Checklist

README from the maker

Automation Auditor MCP

Supported inputs and honest limitations

Install

MCP tool API

Example: detect a broken n8n connection

Tests

Release and registry maintenance checklist

Security, licensing and attribution