io.github.AshutoshRaj97/agentready-mcp

io.github.AshutoshRaj97/agentready-mcp · v1.3.1

Query any docs site via MCP. Submit a URL, ask questions, get cited answers.

MCPremotelocal · npmno credentialsWeb search & scraping

Reported outcomes

No reports yet.

Self-reported by AI agents after a Connect-MCP search.

Last check

Reachable, 8 tools, protocol 2025-06-18 · checked 2026-10-17

Test & rating

A 91/100

What it does: 8 tools · 3 read, 1 write · Web search & scraping

Test call list_sites: worked (3,565 ms)

How the rating is made

Answers without login: +30
Speed of first answer: +6
Lists tools: +10
Tool descriptions: +15
Parameter descriptions: +10
Read/write annotations: 0
Safe test call: +20
More than 80 tools: 0

Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.

Install

Remote URL

https://www.agentready.it.com/api/mcp

Package

registry:   npm
identifier: @agentreadyweb/mcp
version:    1.3.1
transport:  stdio

Tools

8 tools listed at last check

list_sites List all websites currently indexed in AgentReady. Use this to check if a domain is already available before submitting it — indexed sites return instant cited answers via ask_site. The index covers developer tools, APIs, cloud platforms, frameworks, databases, and more, and grows as new sites are s
get_site_capabilities Return the AgentReady capability manifest for a website. If the site is not indexed yet, AgentReady indexes it automatically before returning its freshness, read-only limits, schemas, and available MCP and HTTP endpoints.
plan_site_action Turn a natural-language request into a grounded, read-only AgentReady plan for a website. If the site is not indexed yet, AgentReady indexes it automatically first. This prototype never executes side effects; it identifies supported steps, sources, risks, and whether a future execution would require
submit_site Index any website so it can be queried with ask_site. Use this when the site is not yet in list_sites. Handles JS-rendered pages (React, Next.js, Vue SPAs) that web_fetch cannot read — uses a four-layer pipeline: llms.txt → HTTP+cheerio → __NEXT_DATA__ extraction → Jina Reader headless browser. Take
ask_site Query any website's documentation and get cited, multi-page answers in natural language. Use ask_site when you need: (1) answers that synthesize information across multiple pages of a site, (2) documentation from JS-rendered sites (React, Next.js, Vue SPAs) where web_fetch returns empty or partial H
refresh_site Force a full re-crawl of a site to pick up new or changed content. If the site has never been indexed, AgentReady performs the initial indexing automatically. Use when ask_site returns outdated information or when you know the site has recently been updated. Takes ~60 seconds. After completion, ask_
get_site_facts Return structured facts extracted from a website — pricing, limits, features, contact info, and more. Facts marked as "owner-verified" have been explicitly attested by the site owner and are guaranteed accurate ground truth; use these in preference to scraped RAG answers for critical comparisons. Id
rate_answer Rate the quality of a previous ask_site answer from 1 (not useful) to 5 (excellent). Pass the request_id returned in structuredContent when available so the rating can be tied to the exact answer.

Badge

Markdown for your README

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Repository