Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Audit and generate agent-native product surfaces
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": {
"aigentify": {
"command": "npx",
"args": [
"-y",
"aigentify",
"mcp"
]
}
}
}Run this in your terminal
claude mcp add aigentify -- npx -y aigentify mcpPaste 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.
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.
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 pooriaarab, 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 (0.1.2) reached the registry 3 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, Apify MCP Server
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.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Extract data from any website with thousands of scrapers, crawlers, and automations on Apify Store ⚡
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.
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.
npm install aigentify
Requires Node.js 20 or later. The package has five direct runtime dependencies and includes TypeScript declarations. Price: USD 0.
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.
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.
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.
Scope checked on 2026-10-14. These tools address adjacent auditing needs.
| Scope | aigentify | Lighthouse | axe-core |
|---|---|---|---|
| Primary target | Agent readiness | Web page quality | Accessibility |
| Input here | Directory or URL | Web page | HTML-based interface |
| Generated output here | Agent artifact text | Audit report | Accessibility results |
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 integration | Status | Scope |
|---|---|---|
| AGENTS.md, MCP discovery, server.json | Implemented | Presence, fields, and public-safety heuristics |
| Schema.org offers | Implemented | JSON-LD detection and urgency-language checks |
| llms.txt and sitemap.xml | Implemented | Availability |
| OpenAPI, agent manifests, /agents | Implemented | URL discovery checks |
| Personal Agent Protocol (Poppy) | Implemented | Draft 0.1 validation; discovery-only generator |
| HTTP discovery and crawler responses | Implemented | Markdown, links, status, body, schema, rate-limit headers |
| Authentication guide, API catalog, Agent2Agent card | Implemented | Document shape or availability |
| AI plugin manifest | Implemented | Name, API, and authentication fields |
| Wikidata | Implemented | Official-website lookup |
| npm | Implemented | Package search and name/homepage matching |
| Official MCP Registry | Implemented | Server search and name/host matching |
| Next.js | Template | agents-route --framework next prints route instructions |
External checks return warnings when evidence is missing or inconclusive. URL-only checks return na for local directories.
/agents.md route instructions, then audit the deployed URL.server-json and review its package or remote configuration.audit --json.The library exports auditTarget, formatAuditReport, scoreAuditChecks, defineConfig, defaultConfig, and generator functions. Run the library on Node.js; auditing uses filesystem APIs.
| CLI command | Behavior |
|---|---|
audit [target] | Defaults to .; --json emits the report |
init | Creates AGENTS.md, server.json, and auth.md; --force permits overwrites |
gen | Prints text; --out writes a file |
mcp | Starts 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 }.
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.
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.
aigentify-mcp.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.
aigentify audits a local directory or public URL for agent-readiness signals. Its report contains a score, checks, and actionable gaps.
aigentify implements Wikidata, npm, and Official MCP Registry probes in source. This rewrite checked the implementation, without a live credential-based verification campaign.
aigentify runs in your Node.js process or stdio MCP server. You publish and host the generated artifacts yourself.
aigentify checks agent-facing discovery and generates artifact text. Lighthouse audits web page quality.
aigentify checks agent readiness and public discovery files. axe-core evaluates accessibility in HTML-based interfaces.
aigentify uses no API keys for directory audits or its public registry probes. Generated authentication guides are templates for your product.
aigentify scores implemented heuristics, not end-to-end compatibility with every agent. Test your published interfaces with the clients you support.
aigentify generates text and starter files. You review product facts, implement missing behavior, and deploy the changes.
MIT.