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AgentQL MCP

Turn unstructured web pages into structured data for agents

Web ScrapingfreemiumClaude CodeCursorVS CodeWindsurfEasy

Last verified: August 31, 2026

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How to Install AgentQL MCP

$npx -y agentql-mcp

Requires Claude Desktop, Cursor, Windsurf, or another MCP-compatible client.

About AgentQL MCP

AgentQL's MCP server lets an agent query live web pages semantically and get back structured data, rather than scraping raw HTML and hoping the selectors hold. You describe the shape of the data you want and AgentQL locates it on the page, which makes extraction far more resilient to layout changes than traditional selector-based scraping. A good complement to browser automation servers that can navigate but struggle to parse.

AgentQL MCP is a Web Scraping MCP server designed for developers and AI power users. It enables extending AI assistants with real-world capabilities by exposing a structured set of tools over the Model Context Protocol. Key capabilities include standards-based mcp server interface, works with claude, gpt, gemini, and other mcp clients, tool discovery and structured outputs, and structured tool calls that work cleanly inside an LLM context. It integrates with Claude Desktop, Cursor, Windsurf, and any MCP-compatible client, and is best suited for developers and AI power users who need ai engineers wiring assistants into real tools.

Key Features

  • web-scraping
  • data-extraction
  • structured-data
  • automation
  • Standards-based MCP server interface
  • Works with Claude, GPT, Gemini, and other MCP clients

Pricing

Free
  • Core MCP server
  • Community support
  • Works with any MCP client
Pro
Free tier, usage-based paid plans
  • Everything in Free
  • Higher usage limits
  • Priority support
Business
Custom
  • Everything in Pro
  • SLA & SSO
  • Dedicated support

Tier details are indicative — visit the AgentQL MCP website for current pricing.

Pros & Cons

Pros

  • Drop-in support across MCP-compatible AI clients
  • Reduces prompt boilerplate by exposing concrete tool calls
  • Active community and ongoing updates

Cons

  • Requires an MCP-capable client to use
  • Initial setup can require configuration
  • Capability surface depends on what the underlying service exposes

Best For

  • AI engineers wiring assistants into real tools
  • Teams adopting MCP as an integration standard
  • Power users who want more than chat

Screenshots

Screenshots coming soon —

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Our Take on AgentQL MCP

Solves the brittle-selector problem that makes most scraping setups break within a month. Worth pairing with Playwright or Browserbase rather than treating as a replacement.

Frequently Asked Questions

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