io.github.mlava由 GitHub 账号 mlava 发布v0.7.7更新于 Nov 2, 2026
Scan any URL for AI agent readability — Vercel Spec, llmstxt.org, and agent-protocol manifests.
扫描网址的 AI 智能体可读性，依据 Vercel 规范、llmstxt.org 与智能体协议清单给出评分和逐项修复提示。
Web executable，通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。
把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体，或 SourceWeft 对话中。智能体会读取该服务器的安装指南，先向你展示发布者、端点和登录方式，经你同意后再把它添加到你的客户端。密钥不会写进任何命令。
阅读 https://sourceweft.com/mcp/io.github.mlava%2Fagent-ready-mcp/install.md，并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前，先告诉我它的发布者、端点和登录方式，等我确认。不要把 API 密钥写进命令或我会提交的文件；问我密钥应从哪里获取。把它添加到你客户端的 mcpServers 配置中。
{
"mcpServers": {
"agent-ready": {
"type": "http",
"url": "https://agent-ready.dev/api/v1/mcp"
}
}
}MCP server for Agent Ready — scan any URL for AI agent readability against the Vercel Agent Readability Spec, the llmstxt.org standard, and agent-protocol manifests (MCP server cards, A2A, agents.json, agent-permissions.json, UCP, x402, NLWeb). 72 checks across four spec families — 40 site and page checks (15 site-wide + 25 per-page), 10 against llmstxt.org, and 22 against agent-protocol manifests — each with per-check fix guidance, plus a separate accessibility sub-score from 23 WCAG 2.2 / layout-stability checks.
Hosted at https://agent-ready.dev/api/v1/mcp (Streamable HTTP); this package is a thin stdio wrapper around the same REST endpoints, distributed via npm for local MCP clients (Claude Desktop, Claude Code, Cursor, VS Code, Windsurf).
scan_site — fresh agent-readability scan on any URL. Works without a key on the anonymous free tier (3 scans/30 days per IP, 25-page depth, synchronous); with a Pro key it scans up to 250 pages, polling the hosted API up to 60s.get_scan — fetch a previously-run scan by id (Pro key required — scan history is account-scoped).ask — natural-language (NLWeb) search over Agent Ready's own methodology, checks, and specs. Public, no API key required; returns Schema.org-typed results.validate_structured_data — validate a page's (or a pasted) JSON-LD against Agent Ready's structured-data checks. Public, no API key required; paste mode needs no network, so an agent can check JSON-LD it just authored.scan, interpret_scan, remediation_plan. End-to-end workflows from URL → score → fix-it plan.SKILL.md — Claude Skill descriptor included under skills/agent-ready/ for activation routing.No key is required to start: scan_site, ask, and validate_structured_data all work anonymously out of the box (scan_site on the free anonymous quota — 3 scans per 30 days per IP at 25-page depth). An Agent Ready Pro API key unlocks 50 scans/month, 250-page depth, scan history (get_scan), and weekly monitoring — sign up at agent-ready.dev and issue a key from the dashboard. The env block in the configs below is optional; omit it to run keyless.
Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
.cursor/mcp.json, .vscode/mcp.json, or ~/.codeium/windsurf/mcp_config.json:
A SKILL.md lives at skills/agent-ready/SKILL.md inside the package. To use it in Claude Desktop / Claude Code, copy the skills/agent-ready/ directory into ~/.claude/skills/.
The skill describes when to activate (URL + readability-audit intent), which tool to pick, how to surface scan results without dumping raw JSON, and when to defer to other tools (general SEO, performance profiling, code editing).
This package is a thin stdio→HTTPS wrapper:
All scan execution, persistence, and Pro-tier quota enforcement happen on the hosted server. The npm package only translates between MCP JSON-RPC over stdio and the REST API.
If you'd rather use the hosted MCP server directly (Streamable HTTP transport, no local install), point your MCP client at https://agent-ready.dev/api/v1/mcp with Authorization: Bearer ar_live_....
The 72 checks, their weights, and the score formula are documented at agent-ready.dev/methodology. Both manifest.json and server.json in this repo conform to the relevant registry schemas (Glama Marketplace v0.3 and MCP registry 2025-12-11 respectively).
See RELEASE.md. It is the source of truth for version surfaces, local checks, tag pushing, the GitHub Actions release workflow, and the manual post-release steps.
MIT — see LICENSE.
来源：README.md，提交 ab4818b
Scan a site for AI agent readability
Runs the agent-ready.dev scanner against a URL and returns structured results: Vercel score, llmstxt.org score, and per-check findings with remediation hints. Scans may take up to ~60s; for larger scans the tool returns a scan id and asks you to poll with get_scan.
url必填pageLimitGet a previous scan by id
Fetches a completed or in-progress scan by its id. Only scans owned by the authenticated API key's user are returned.
id必填Ask Agent Ready in natural language
Natural-language search (NLWeb /ask) over Agent Ready's own content — scoring methodology, the check registry, the specs it validates, and the content library (explainers, comparisons, how-to guides, glossary). Returns Schema.org-typed result objects. Optional itemType narrows to a corpus type; mode 'summarize' adds an extractive summary.
q必填modeitemType已满足适用检查项的 100%
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。
{ "mcpServers": { "agent-ready": { "command": "npx", "args": ["-y", "agent-ready-mcp@latest"], "env": { "AGENT_READY_API_KEY": "ar_live_..." } } }}claude mcp add agent-ready \ -e AGENT_READY_API_KEY=ar_live_... \ -- npx -y agent-ready-mcp@latest{ "mcpServers": { "agent-ready": { "command": "npx", "args": ["-y", "agent-ready-mcp@latest"], "env": { "AGENT_READY_API_KEY": "ar_live_..." } } }}You: Use agent-ready to scan https://my-saas.comClaude: [calls scan_site] Your site scored 78/100 (Good) on the Vercel Agent Readability Spec. The top 3 fixes: …You: Can you build me a remediation plan?Claude: [calls remediation_plan with the scan id] Here's the prioritised list…MCP client (stdio) ↔ agent-ready-mcp ↔ HTTPS ↔ agent-ready.dev/api/v1/scansnpm installnpm run build # → dist/mcp-server.mjsnpm testnpm run typecheck