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aigentify

aigentify audits a product directory or live URL for agent-native readiness. It also creates the public artifacts that agents can use.

Install

npm install aigentify

Related MCP server: AI Knowledge Center MCP

Three faces

Use the library in JavaScript or TypeScript:

import { auditTarget, generate } from 'aigentify';

const report = await auditTarget('.');
const instructions = generate('agents-md', {
  name: 'Example product',
  description: 'A product with a clear agent interface.',
  repository: 'https://github.com/example/product',
});

Use the CLI:

npx aigentify audit .
npx aigentify gen agents-md
npx aigentify gen server-json --out server.json

Use the MCP server with an MCP client:

npx aigentify-mcp

The MCP server exposes audit with { target } and gen with { artifact, params }.

Commands

  • aigentify audit [target] checks a directory or URL. The default target is ..

  • aigentify init writes starter AGENTS.md and server.json files. Existing files stay unchanged.

  • aigentify gen <artifact> prints an artifact or writes it with --out.

  • aigentify mcp starts the stdio MCP server.

Artifacts are agents-md, server-json, offer, and agents-route.

Configuration

Add an optional aigentify.config.ts, aigentify.config.js, or aigentify.config.mjs file. Export defineConfig(...) data as the default export or as aigentifyConfig.

import { defineConfig } from 'aigentify';

export default defineConfig({
  name: 'Example product',
  description: 'A product with a clear agent interface.',
  repository: 'https://github.com/example/product',
  npmPackage: 'example-product',
  offer: { name: 'Access', price: 0, priceCurrency: 'USD' },
});

License

MIT

A
license - permissive license
-
quality - not tested
B
maintenance

Maintenance

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