AgentQL▌

by tinyfish-io
AgentQL lets you scrape any website and extract structured data to JSON easily—no custom web scraping code needed.
Extracts structured data from web pages based on natural language descriptions, converting website content into JSON format without custom scraping code.
best for
- / Data analysts gathering web information
- / Researchers collecting structured datasets
- / Developers building data pipelines
- / Anyone needing web scraping without coding
capabilities
- / Extract structured data from web pages
- / Convert website content to JSON format
- / Describe data fields in natural language
- / Scrape without writing custom code
- / Parse complex web layouts automatically
what it does
Extracts structured data from any web page using plain English descriptions instead of writing custom scraping code. Returns clean JSON data based on what you ask for.
about
AgentQL is an official MCP server published by tinyfish-io that provides AI assistants with tools and capabilities via the Model Context Protocol. AgentQL lets you scrape any website and extract structured data to JSON easily—no custom web scraping code needed. It is categorized under search web.
how to install
You can install AgentQL in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
AgentQL is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
AgentQL MCP Server
This is a Model Context Protocol (MCP) server that integrates AgentQL's data extraction capabilities.
Features
Tools
extract-web-data- extract structured data from a given 'url', using 'prompt' as a description of actual data and its fields to extract.
Installation
To use AgentQL MCP Server to extract data from web pages, you need to install it via npm, get an API key from our Dev Portal, and configure it in your favorite app that supports MCP.
Install the package
npm install -g agentql-mcp
Configure Claude
- Open Claude Desktop Settings via
⌘+,(don't confuse with Claude Account Settings) - Go to Developer sidebar section
- Click Edit Config and open
claude_desktop_config.jsonfile - Add
agentqlserver insidemcpServersdictionary in the config file - Restart the app
{
"mcpServers": {
"agentql": {
"command": "npx",
"args": ["-y", "agentql-mcp"],
"env": {
"AGENTQL_API_KEY": "YOUR_API_KEY"
}
}
}
}
Read more about MCP configuration in Claude here.
Configure VS Code
For one-click installation, click one of the install buttons below:
Manual Installation
Click the install buttons at the top of this section for the quickest installation method. For manual installation, follow these steps:
Add the following JSON block to your User Settings (JSON) file in VS Code. You can do this by pressing Ctrl + Shift + P and typing Preferences: Open User Settings (JSON).
{
"mcp": {
"inputs": [
{
"type": "promptString",
"id": "apiKey",
"description": "AgentQL API Key",
"password": true
}
],
"servers": {
"agentql": {
"command": "npx",
"args": ["-y", "agentql-mcp"],
"env": {
"AGENTQL_API_KEY": "${input:apiKey}"
}
}
}
}
}
Optionally, you can add it to a file called .vscode/mcp.json in your workspace. This will allow you to share the configuration with others.
{
"inputs": [
{
"type": "promptString",
"id": "apiKey",
"description": "AgentQL API Key",
"password": true
}
],
"servers": {
"agentql": {
"command": "npx",
"args": ["-y", "agentql-mcp"],
"env": {
"AGENTQL_API_KEY": "${input:apiKey}"
}
}
}
}
Configure Cursor
- Open Cursor Settings
- Go to MCP > MCP Servers
- Click + Add new MCP Server
- Enter the following:
- Name: "agentql" (or your preferred name)
- Type: "command"
- Command:
env AGENTQL_API_KEY=YOUR_API_KEY npx -y agentql-mcp
Read more about MCP configuration in Cursor here.
Configure Windsurf
- Open Windsurf: MCP Configuration Panel
- Click Add custom server+
- Alternatively you can open
~/.codeium/windsurf/mcp_config.jsondirectly - Add
agentqlserver insidemcpServersdictionary in the config file
{
"mcpServers": {
"agentql": {
"command": "npx",
"args": ["-y", "agentql-mcp"],
"env": {
"AGENTQL_API_KEY": "YOUR_API_KEY"
}
}
}
}
Read more about MCP configuration in Windsurf here.
Validate MCP integration
Give your agent a task that will require extracting data from the web. For example:
Extract the list of videos from the page https://www.youtube.com/results?search_query=agentql, every video should have a title, an author name, a number of views and a url to the video. Make sure to exclude ads items. Format this as a markdown table.
[!TIP] In case your agent complains that it can't open urls or load content from the web instead of using AgentQL, try adding "use tools" or "use agentql tool" hint.
Development
Install dependencies:
npm install
Build the server:
npm run build
For development with auto-rebuild:
npm run watch
If you want to try out development version, you can use the following config instead of the default one:
{
"mcpServers": {
"agentql": {
"command": "/path/to/agentql-mcp/dist/index.js",
"env": {
"AGENTQL_API_KEY": "YOUR_API_KEY"
}
}
}
}
[!NOTE] Don't forget to remove the default AgentQL MCP server config to not confuse Claude with two similar servers.
Debugging
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:
npm run inspector
The Inspector will provide a URL to access debugging tools in your browser.