Agentready Mcp
📇 ☁️ 🍎 🪟 🐧 - Make any website queryable by AI agents. Index a site then ask questions and get cited answers grounded in its content via RAG. Tools: listsites and asksite. npx -y @agentreadyweb/mcp
Quick Install
{
"mcpServers": {
"ashutoshraj97-agentready-mcp": {
"command": "npx",
"args": [
"-y",
"ashutoshraj97-agentready-mcp"
]
}
}
}Using an AI coding agent (Claude Code, Cursor, etc.)? Copy a ready-made prompt that tells it to fetch the setup instructions and install this server for you.
Documentation Overview
@agentreadyweb/mcp
What is AgentReady?
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:
- Works on any public URL — static sites, React/Next.js SPAs, Docusaurus, GitBook, custom engines
- No account required to index your first site
- Shared index — one team member submits a site, everyone on the team can query it instantly
- Handles JS-rendered pages that
web_fetchreturns empty for - Capability manifests expose freshness, schemas, endpoints, and read-only limits
- Grounded plans return evidence, risks, confirmation requirements, and durable receipts
Built with Codex and GPT-5.6
Codex, powered by GPT-5.6, was used throughout development as an engineering copilot. It helped extend and test the MCP server, automatic indexing flows, capability manifests, safe action planning, CLI commands, documentation, and production integrations.
The MCP package is model-agnostic at the client boundary. GPT-5.6 supported development, testing, and iteration without being required by the end user's MCP client.
CLI
The 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
# Ask any site a question, get a cited answer (auto-indexes new sites in ~60s)
npx @agentreadyweb/mcp ask stripe.com "what is the test card number?"
# Index or re-crawl a site
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
- run: npx @agentreadyweb/mcp refresh yourdocs.com
Connect any MCP-compatible client to AgentReady:
Local MCP bridge (stdio)
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 seven tools available:
list_sites— see all indexed websitesget_site_capabilities— index on demand, then inspect a site manifest, freshness, schemas, and endpointsask_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 feedback
Cursor
Add to ~/.cursor/mcp.json:
{
"agentready": {
"command": "npx",
"args": ["-y", "@agentreadyweb/mcp"]
}
}
Project or terminal setup
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"]
}
}
}
VS Code (GitHub Copilot agent mode)
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.
Windsurf / Zed / other clients
Any MCP client that supports stdio transport works the same way — use npx -y @agentreadyweb/mcp as the command.
WebMCP (no install)
If your client supports HTTP transport, connect directly by URL — no npm required:
https://www.agentready.it.com/api/mcp
Docusaurus plugin
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' }]
]
MkDocs plugin
If your docs site uses MkDocs, auto-index on every build:
pip install mkdocs-agentready
# mkdocs.yml
plugins:
- search
- agentready
If site_url is not set, specify the domain explicitly:
plugins:
- agentready:
domain: docs.yoursite.com
Starlight plugin
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()],
}),
],
})
Sphinx extension
If your docs site uses Sphinx, auto-index on every build:
pip install sphinx-agentready
# conf.py
extensions = [
"sphinx_agentready.extension",
]
# Domain is inferred from html_baseurl automatically, or set explicitly:
agentready_domain = "docs.yoursite.com"
Available tools
list_sites
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
get_site_capabilities(domain: string)
Returns the site's capability manifest, freshness state, schemas, and available HTTP/MCP endpoints.
plan_site_action
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
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
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
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
rate_answer(domain: string, rating: number, request_id?: string, comment?: string)
Submits 1–5 quality feedback, optionally tied to the exact ask_site request.
Deploy webhook
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
How indexing works
AgentReady uses a layered approach to handle any public website:
- llms.txt / llms-full.txt — if the site publishes one, it's used as a high-quality structured content source
- Standard HTML crawl — fetches up to 10 pages via sitemap or link crawling, extracts clean text
__NEXT_DATA__extraction — for Next.js apps, parses server-side rendered data embedded in the HTML- Jina Reader fallback — for JS-only SPAs that return empty HTML, uses a remote rendering service to extract content
Sites behind authentication or with no public HTML content cannot be indexed.
Environment variables
| Variable | Default | Description |
|---|---|---|
AGENTREADY_MCP_URL | https://www.agentready.it.com/api/mcp | Override the MCP endpoint (for self-hosted) |