Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Query any docs site via MCP. Submit a URL, ask questions, get cited answers.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
AGENTREADY_MCP_URL你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
适用于网页版、桌面版和手机版 Claude:
https://www.agentready.it.com/api/mcp打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"agentready": {
"command": "npx",
"args": [
"-y",
"@agentreadyweb/mcp"
],
"env": {
"AGENTREADY_MCP_URL": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add --transport http agentready https://www.agentready.it.com/api/mcpclaude mcp add agentready --env AGENTREADY_MCP_URL=your-value -- npx -y @agentreadyweb/mcp运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"agentready": {
"url": "https://www.agentready.it.com/api/mcp"
}
}
}粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"agentready": {
"command": "npx",
"args": [
"-y",
"@agentreadyweb/mcp"
],
"env": {
"AGENTREADY_MCP_URL": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"agentready": {
"type": "http",
"url": "https://www.agentready.it.com/api/mcp"
}
}
}粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"agentready": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@agentreadyweb/mcp"
],
"env": {
"AGENTREADY_MCP_URL": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
ChatGPT 只能连接互联网上的服务器:
https://www.agentready.it.com/api/mcp菜单名称可能因套餐和版本不同而略有差异。
你的选择通过 Cookie 保存在这台设备上,无需账户。
AGENTREADY_MCP_URL env这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 AshutoshRaj97 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
两种方式都可以:安装在你的电脑上,或者连接云端版本。
GitHub 仓库最后更新于–,最新版本(1.3.1)于3个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:Spec Driven Development, Remote Desktop Commander, NexusWindows
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
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.
Windows computer use in the background: desktop apps driven without your mouse or keyboard.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
AgentReady is a hosted capability layer that makes any website discoverable and usable by agents through MCP.
Paste a URL → AgentReady crawls the site, generates a spec-compliant llms.txt, and hosts a live /ask RAG endpoint and MCP server. Any MCP-compatible agent client can then discover the site, ask natural-language questions, inspect capabilities, and create grounded read-only plans with citations.
The problem it solves: AI agents using web_fetch fetch one page at a time, get empty HTML from JavaScript SPAs (React, Next.js, Vue), and hallucinate when the answer spans multiple pages. AgentReady indexes the whole site, handles JS rendering, and retrieves across pages — so agents get the right answer instead of a confident wrong one.
What's already indexed: Browse the live AgentReady directory → or index any public site yourself.
Key properties:
web_fetch returns empty forThe same package doubles as a CLI — no install, no account:
# Agent-readiness report card (llms.txt, sitemap, robots, JS-rendering, index status)
npx @agentreadyweb/mcp grade yourdocs.com
npx @agentreadyweb/mcp ask stripe.com "what is the test card number?"
npx @agentreadyweb/mcp index yourdocs.com npx @agentreadyweb/mcp refresh yourdocs.com
For CI, dashboards, or scripts, add --json to receive the raw report on stdout (progress remains on stderr):
npx @agentreadyweb/mcp grade yourdocs.com --json | jq '.grade, .score'
The command still exits 1 when the grade is below B.
grade exits non-zero below a B, so you can use it as a CI gate. refresh in your docs deploy pipeline keeps the index fresh automatically:
# GitHub Actions — after your docs deploy step
Connect any MCP-compatible client to AgentReady:
For clients that use an mcpServers configuration, add the AgentReady bridge:
{
"mcpServers": { "agentready": { "command": "npx", "args": ["-y", "@agentreadyweb/mcp"] } } }
Restart your client. You'll have eight tools available:
list_sites — see all indexed websitesget_site_capabilities — index on demand, then inspect a site manifest, freshness, schemas, and endpointsget_site_facts — key structured facts extracted from a siteask_site — query any site with cited, multi-page answersplan_site_action — index on demand, then create a grounded, read-only plan and receiptsubmit_site — index any website so it can be queriedrefresh_site — re-crawl a site, or perform its initial index when it is newrate_answer — submit quality feedbackAdd to ~/.cursor/mcp.json:
{
"agentready": { "command": "npx", "args": ["-y", "@agentreadyweb/mcp"] } }
npx @agentreadyweb/mcp
Or add the same agentready server to your client's project configuration to share it with your team:
{
"mcpServers": { "agentready": { "command": "npx", "args": ["-y", "@agentreadyweb/mcp"] } } }
Requires VS Code 1.99+ with the GitHub Copilot extension. Create .vscode/mcp.json in your project root:
{
"servers": { "agentready": { "type": "stdio", "command": "npx", "args": ["-y", "@agentreadyweb/mcp"] } } }
Copilot's MCP tools are only available in agent mode. Commit this file to share with your team.
Any MCP client that supports stdio transport works the same way — use npx -y @agentreadyweb/mcp as the command.
If your client supports HTTP transport, connect directly by URL — no npm required:
https://www.agentready.it.com/api/mcp
If your docs site uses Docusaurus, auto-index on every build:
npm install @agentreadyweb/docusaurus-plugin
// docusaurus.config.js
plugins: [ ['@agentreadyweb/docusaurus-plugin', { domain: 'docs.yoursite.com' }] ]
If your docs site uses MkDocs, auto-index on every build:
pip install mkdocs-agentready
# mkdocs.yml
plugins:
If site_url is not set, specify the domain explicitly:
plugins:
If your docs site uses Starlight (Astro), auto-index on every build:
npm install starlight-agentready
// astro.config.mjs
import agentready from 'starlight-agentready'
export default defineConfig({ site: 'https://docs.yoursite.com', integrations: [ starlight({ plugins: [agentready()], }), ], })
If your docs site uses Sphinx, auto-index on every build:
pip install sphinx-agentready
# conf.py
extensions = [ "sphinx_agentready.extension", ]
agentready_domain = "docs.yoursite.com"
Lists all websites currently indexed by AgentReady with their titles and page counts. Use this to check if a domain is already available before submitting it.
get_site_capabilities(domain: string)
Returns the site's capability manifest, freshness state, schemas, and available HTTP/MCP endpoints.
get_site_facts(domain: string)
Returns key structured facts extracted from a site — pricing tiers, feature lists, limits, and other high-signal data points that agents frequently need.
plan_site_action(domain: string, request: string)
Creates a grounded, read-only plan with evidence, risks, confirmation requirements, and a durable receipt. It does not execute side effects.
submit_site(url: string)
Index any website with AgentReady. Takes ~60 seconds. Handles static sites, server-rendered pages, and JavaScript-heavy SPAs via a four-layer pipeline. Once done, query it with ask_site.
Example: submit_site("https://docs.example.com")
ask_site(domain: string, query: string, url?: string)
Ask a question about any website and get a cited answer grounded in its content. Synthesises information across multiple pages. If the site isn't indexed yet, AgentReady crawls and indexes it automatically before answering (~60s).
Example: ask_site("stripe.com", "What are the fees for card payments?")
refresh_site(domain: string)
Force a full re-crawl of a site to pick up new or changed content. If the site is new, AgentReady performs its initial index automatically. Takes ~60 seconds.
Example: refresh_site("docs.example.com")
rate_answer(domain: string, rating: number, request_id?: string, comment?: string)
Submits 1–5 quality feedback, optionally tied to the exact ask_site request.
Automatically re-index your docs on every deploy. No auth required — rate limited to once per hour per domain.
curl -X POST https://www.agentready.it.com/api/webhook/refresh \
-H "Content-Type: application/json" \ -d '{"domain": "docs.yoursite.com"}'
Or pass the domain as a query param (works with Vercel/Netlify form-encoded webhook payloads):
https://www.agentready.it.com/api/webhook/refresh?domain=docs.yoursite.com
AgentReady uses a layered approach to handle any public website:
Sites behind authentication or with no public HTML content cannot be indexed.
| Variable | Default | Description |
|---|---|---|
AGENTREADY_MCP_URL | https://www.agentready.it.com/api/mcp | Override the MCP endpoint (for self-hosted) |
AGENTREADY_TELEMETRY | 1 | Set to 0 to disable anonymous usage telemetry |
This package sends a lightweight anonymous ping to agentready.it.com/api/telemetry each time the MCP bridge starts or a CLI command runs. It contains: a random install ID (stored in ~/.agentready/install-id), package version, Node version, platform, and which mode/command was used. No query content, no domain names, no personal data. Set AGENTREADY_TELEMETRY=0 to opt out.