
Aigentify
io.github.pooriaarab由 GitHub 账号 pooriaarab 发布v0.1.2更新于 Oct 24, 2026
Audit and generate agent-native product surfaces
发布方自己的服务:AI Benchmark Index
概览
审查产品目录或线上网址对智能体的友好程度,并生成 AGENTS.md、server.json 等面向智能体的产物。
- 可以做什么
- Aigentify 提供两个 MCP 工具:audit 接收目录或网址,评估 agents-md、server-json、mcp、llms-txt、sitemap 等信号,对网址还会检查 openapi、soft-404、markdown-negotiation、rate-limit 头等;gen 生成 agents-md、server-json、offer、agents-route 四类产物。部分网址检查会查询第三方注册表以做外部发现。相同功能也以 JavaScript/TypeScript 库和命令行形式提供。
- 适用场景
- 当你希望助手评估某个产品或网站是否便于智能体发现和使用,或起草使其达标的标准文件时使用。适合为智能体准备文档、清单或发现元数据的开发者。
- 运行要求
- 以 stdio 方式在本地运行,通常用 npx aigentify-mcp 或 aigentify mcp 命令启动。需要 Node.js;处理网址目标和外部发现检查时需要网络访问。未声明账号、API 密钥或环境变量。
安装
在 SourceWeft 中
- 打开 控制台中的 Aigentify,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
aigentify
[npm version] [downloads/month] [license]
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
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:
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:
Success creates agents.md. Review its placeholders and product-specific instructions before publishing it.
Save this as audit.mjs and run node audit.mjs to print the score and structured offer.
How it works
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
- Package maintainers audit a Node.js directory before publishing agent-facing files to npm.
- Next.js developers generate
/agents.mdroute instructions, then audit the deployed URL. - MCP server authors generate
server-jsonand review its package or remote configuration. - API teams inspect OpenAPI discovery, authentication guides, and Agent2Agent cards on a public URL.
- 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:
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.
来源:README.md,提交 822a4d9
工具
0版本历史
1- v0.1.2最新Sep 16, 2026
评分
已满足适用检查项的 50%
该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。
- 近 30 天内可连通25 分
请保持端点能够响应 MCP 握手;SourceWeft 每 30 天探测一次。
- 已声明认证方式10 分
请在注册中心条目中声明凭据请求头,或保持端点能够响应探测,以便判定其认证方式。
- 已列出工具15 分
请让服务器在无凭据时响应 tools/list,或发布可在沙箱中无凭据启动的软件包。
- 描述必需15 分
- 图标10 分
- 文档15 分
- 许可证10 分
其他 Aibenchmarkindex 集成

AI Benchmark Index
com.aibenchmarkindex官方发布者
AI Benchmark Index 的远程 MCP 端点,让助手按文本、地点和类别检索已发布的 AI 基准测试,并查看其数据来源。

Surrogacyagencies
由 GitHub 账号 pooriaarab 发布
为您的旅程寻找代孕机构和组织。AI 翻译

Quantumcompanies
由 GitHub 账号 pooriaarab 发布
Quantumcompanies 的托管 MCP 服务;无需登录;Streamable HTTP;9 个工具。

Liquidcooling
由 GitHub 账号 pooriaarab 发布
为30-150 kW的AI数据中心寻找液冷供应商。AI 翻译

Goldenvisas
由 GitHub 账号 pooriaarab 发布
查找通过投资获得居留权和公民身份的授权代理。AI 翻译