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

Aigentify

by pooriaarabversion 0.1.2i★ –iRuns on your computer
Registry nameio.github.pooriaarab/aigentify

Install

Overview

Description from the maker (original English)

Audit and generate agent-native product surfaces

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

  • npmNode.js installed (for the npx 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": {
    "aigentify": {
      "command": "npx",
      "args": [
        "-y",
        "aigentify",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add aigentify -- npx -y aigentify mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "aigentify": {
      "command": "npx",
      "args": [
        "-y",
        "aigentify",
        "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": {
    "aigentify": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "aigentify",
        "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 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account pooriaarab, 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 32435 servers in this category
  • Published to the registry more recently than 24% of the other 32435 servers in this category
  • Basic checks equal to or better than 100% of the other 32435 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 Aigentify 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 (0.1.2) reached the registry 3 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Apify MCP Server

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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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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Extract data from any website with thousands of scrapers, crawlers, and automations on Apify Store ⚡

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.

aigentify

Package and API types · Quickstart · Configuration

aigentify is an open-source agent-readiness auditing tool for developers who maintain product directories and public websites. It returns a score, individual checks, and actionable gaps. Its TypeScript library, command-line interface (CLI), and Model Context Protocol (MCP) server also generate public artifact text.

Install

npm install aigentify

Requires Node.js 20 or later. The package has five direct runtime dependencies and includes TypeScript declarations. Price: USD 0.

Run your first audit

Run this command from an existing product directory:

npx aigentify audit .

No environment variables, credentials, or .env loader are required for a directory audit. The report starts with .: /100, lists check statuses, and ends with Gaps:. A low score is a completed audit, not a command failure.

Generate a public guide with your product facts:

npx aigentify gen agents-md --name Example --description 'A product API.' --repository https://example.com --price 0 --price-currency USD --out agents.md

Success creates agents.md. Review its placeholders and product-specific instructions before publishing it.

import { auditTarget, generate } from 'aigentify';

const report = await auditTarget('.'); console.log(report.score, report.gaps); console.log(generate('offer', { name: 'Example', description: 'A product API.', repository: 'https://example.com', offer: { price: 0, priceCurrency: 'USD' }, }));

Save this as audit.mjs and run node audit.mjs to print the score and structured offer.

How it works

Directory files or URL responses

| Snapshot and checks | Score + ordered gaps | Fix product facts -> generate text -> publish -> audit again

URL audits fetch discovery endpoints and query external registries. Directory audits inspect files without running the application.

Why it exists

Developers need to check agent discovery files alongside ordinary website checks. Lighthouse audits web quality; axe-core checks accessibility. aigentify focuses on agent-facing manifests, public instructions, offers, and discovery evidence.

Compare

Scope checked on 2026-10-14. These tools address adjacent auditing needs.

ScopeaigentifyLighthouseaxe-core
Primary targetAgent readinessWeb page qualityAccessibility
Input hereDirectory or URLWeb pageHTML-based interface
Generated output hereAgent artifact textAudit reportAccessibility results

Coverage

The implementation defines 27 audit checks, six generators, and three external registry probes. These are source-checked capabilities, not evidence that every target passes them. No credential-based platform verification was performed for this rewrite.

Surface or integrationStatusScope
AGENTS.md, MCP discovery, server.jsonImplementedPresence, fields, and public-safety heuristics
Schema.org offersImplementedJSON-LD detection and urgency-language checks
llms.txt and sitemap.xmlImplementedAvailability
OpenAPI, agent manifests, /agentsImplementedURL discovery checks
Personal Agent Protocol (Poppy)ImplementedDraft 0.1 validation; discovery-only generator
HTTP discovery and crawler responsesImplementedMarkdown, links, status, body, schema, rate-limit headers
Authentication guide, API catalog, Agent2Agent cardImplementedDocument shape or availability
AI plugin manifestImplementedName, API, and authentication fields
WikidataImplementedOfficial-website lookup
npmImplementedPackage search and name/homepage matching
Official MCP RegistryImplementedServer search and name/host matching
Next.jsTemplateagents-route --framework next prints route instructions

External checks return warnings when evidence is missing or inconclusive. URL-only checks return na for local directories.

Common use cases

  1. Package maintainers audit a Node.js directory before publishing agent-facing files to npm.
  2. Next.js developers generate /agents.md route instructions, then audit the deployed URL.
  3. MCP server authors generate server-json and review its package or remote configuration.
  4. API teams inspect OpenAPI discovery, authentication guides, and Agent2Agent cards on a public URL.
  5. Product developers check Wikidata, npm, and Official MCP Registry discovery evidence.

Features

  • Directory and URL audits return scores, checks, and ordered gaps.
  • Artifact generation returns text without deploying a service.
  • JSON output supports scripts through audit --json.
  • Configuration shares product facts across generated artifacts.

Runtime surfaces

The library exports auditTarget, formatAuditReport, scoreAuditChecks, defineConfig, defaultConfig, and generator functions. Run the library on Node.js; auditing uses filesystem APIs.

CLI commandBehavior
audit [target]Defaults to .; --json emits the report
initCreates AGENTS.md, server.json, and auth.md; --force permits overwrites
gen Prints text; --out writes a file
mcpStarts the stdio server

The six artifact names are agents-md, server-json, offer, agents-route, auth-md, and poppy. agents-route accepts --framework static or --framework next.

Start the standalone server with npx aigentify-mcp. Its two tools are audit with { target } and gen with { artifact, params }.

Configuration

Create aigentify.config.ts, aigentify.config.js, or aigentify.config.mjs for CLI generation:

import { defineConfig } from 'aigentify';

export default defineConfig({ name: 'Example', description: 'A product API.', repository: 'https://example.com', npmPackage: 'example-product', offer: { price: 0, priceCurrency: 'USD' }, });

Export a default configuration or a named aigentifyConfig. Library and MCP generation accept parameters directly.

Delivery/behavior limits

Scores use weighted heuristics. A perfect score does not guarantee agent compatibility, search ranking, or discovery. The crawler check uses one agent User-Agent; it does not test every crawler. Requests have eight-second timeouts; registry failures can leave discovery evidence inconclusive. Audits fetch text without executing browser JavaScript. Generated files contain defaults and templates that require review. The authentication template describes API-key behavior; it does not implement authentication. The Poppy generator emits discovery-only data, not authenticated agent or API connections. init preserves existing files unless --force is set. It does not deploy them.

Integration guides

  • Next.js route template: generate instructions, then publish the route yourself.
  • MCP stdio setup: connect a client to aigentify-mcp.
  • Shared product configuration: set names, URLs, and offer facts.

Status

Version 0.5.0 is a 0.x release. Interfaces and checks can change. Use the GitHub issue channel listed on the npm package for support. Public case studies are not yet published in this README.

FAQ

What does aigentify audit?

aigentify audits a local directory or public URL for agent-readiness signals. Its report contains a score, checks, and actionable gaps.

Which integrations are verified?

aigentify implements Wikidata, npm, and Official MCP Registry probes in source. This rewrite checked the implementation, without a live credential-based verification campaign.

Does aigentify provide a managed service?

aigentify runs in your Node.js process or stdio MCP server. You publish and host the generated artifacts yourself.

How is aigentify different from Lighthouse?

aigentify checks agent-facing discovery and generates artifact text. Lighthouse audits web page quality.

How is aigentify different from axe-core?

aigentify checks agent readiness and public discovery files. axe-core evaluates accessibility in HTML-based interfaces.

Does aigentify need API keys?

aigentify uses no API keys for directory audits or its public registry probes. Generated authentication guides are templates for your product.

Does a score of 100 guarantee compatibility?

aigentify scores implemented heuristics, not end-to-end compatibility with every agent. Test your published interfaces with the clients you support.

Can aigentify fix my website automatically?

aigentify generates text and starter files. You review product facts, implement missing behavior, and deploy the changes.

License

MIT.

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