mcp server
agentready-mcp
Query any docs site via MCP. Submit a URL, ask questions, get cited answers.
Description as published by the maintainer. Source
- version 1.3.0
- active
active — Most recent push to the repository was 2026-07-21.
What this server can do
8 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.
ask_site(url, query, domain)- 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 HTML, (3) citations linking back to the exact source pages, (4) faster results than fetching and reading individual pages one by one. For sites not yet indexed, ask_site auto-crawls and answers in ~60s — no separate submit_site call needed. Required: domain, query.
get_site_capabilities(domain)- 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. Required: domain.
get_site_facts(domain, category)- 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. Ideal for price comparison across multiple sites, feature matrix lookups, or any task where you need structured data rather than a natural-language synthesis. Required: domain.
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 submitted.
plan_site_action(domain, request)- 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 confirmation. Required: domain, request.
rate_answer(domain, rating, comment, request_id)- 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. Required: domain, rating.
refresh_site(domain)- 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_site returns fresh content. Required: domain.
submit_site(url)- 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. Takes ~60 seconds. Once indexed, ask_site queries are instant. Required: url.
Last successful function declaration observed on . Source: https://www.agentready.it.com/api/mcp. We list what the server declared; we do not call any of these functions.
Endpoint status observed on . Source: https://www.agentready.it.com/api/mcp.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| GitHub stars | 2 | Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. | cumulative, all time | GitHub | |
| Last commit | 2026-07-21 | Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. | point in time | GitHub | |
| Open issues | 0 | Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. | as of fetch | GitHub | |
| Latest published version | 1.3.0 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-07-20 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| First listed in the MCP Registry | 2026-07-20 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| repository status | active | The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. | as of fetch | GitHub | |
| mcp tools declared | 8 tools | Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. | as of probe | www.agentready.it.com | |
| mcp endpoint status | ok | The server listed 8 functions when asked. | as of probe | www.agentready.it.com |
Where to get it
This record as data
Every field on this page, with its source and observation date, is in the catalog JSON. Fetch the whole kind at once instead of parsing this HTML.
GET /api/v1/entries/mcp_server.json