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.

Related MCP server: AI Knowledge Center MCP

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 .: <score>/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.

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.

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.

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.