MCP server

AgentReady

io.github.AshutoshRaj97/agentready-mcp

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

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

Source

At a glance

Type

MCP server

Publisher

Not verified

Status

Working at last check

Tools

8

Token cost

About 1,518 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http agentready-mcp https://www.agentready.it.com/api/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.agentready-mcp]
url = "https://www.agentready.it.com/api/mcp"

Gemini CLI

{"mcpServers":{"agentready-mcp":{"httpUrl":"https://www.agentready.it.com/api/mcp"}}}

Cursor

{"mcpServers":{"agentready-mcp":{"url":"https://www.agentready.it.com/api/mcp"}}}

VS Code

{"servers":{"agentready-mcp":{"type":"http","url":"https://www.agentready.it.com/api/mcp"}}}

Antigravity

agy mcp add agentready-mcp https://www.agentready.it.com/api/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"agentready-mcp","server_url":"https://www.agentready.it.com/api/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"agentready-mcp","server_url":"https://www.agentready.it.com/api/mcp"}

Tools

• ask_site ~298 tokens
  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
• get_site_capabilities ~137 tokens
  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.
• get_site_facts ~247 tokens
  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
• list_sites ~118 tokens
  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
• plan_site_action ~197 tokens
  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
• rate_answer ~199 tokens
  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.
• refresh_site ~154 tokens
  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_
• submit_site ~168 tokens
  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

Browse

• GitHub tools
• AgentReady tools
• Web scraping
• Browser automation
• GitHub and code hosting
• Searching your documents (RAG)

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