Scrapegraph MCP

Name: Scrapegraph MCP
Author: ScrapeGraphAI

作者：ScrapeGraphAI版本 1.0.1i★ –i在你的电脑上运行

注册名称io.github.ScrapeGraphAI/scrapegraph-mcp

安装

概览

作者提供的说明（英文原文）

AI-powered web scraping and data extraction capabilities through ScrapeGraph API

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数：意见、测量和人气是不同的东西。

用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
我们的基础检查i1 项中通过 1 项依据公开信息检查；尚未扫描代码
使用情况i尚未统计★ –

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

连接方式: 在你的电脑上运行
传输方式: stdio
分类: 网页与浏览器
你需要填写：SGAI_API_KEY

安装

选择你使用的 AI 应用，然后复制设置。

安装之前

基础检查：1 项中通过 1 项
在你的电脑上运行，拥有你的用户账户的权限（文件、网络、应用）。
需要你自己填写： SGAI_API_KEY

标为机密的值是你账户的钥匙。千万不要分享给别人，也不要粘贴到聊天里。

你需要

PyPI已安装 Python 的 uv（用于 uvx 命令）

你用的是哪个应用？

ClaudeClaude CodeCursorVS CodeChatGPT

在上方选择你的应用。我们会记住它，下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config，把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "scrapegraph": {
      "command": "uvx",
      "args": [
        "scrapegraph-mcp"
      ],
      "env": {
        "SGAI_API_KEY": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add scrapegraph --env SGAI_API_KEY=your-value -- uvx scrapegraph-mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json，或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "scrapegraph": {
      "command": "uvx",
      "args": [
        "scrapegraph-mcp"
      ],
      "env": {
        "SGAI_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "scrapegraph": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "scrapegraph-mcp"
      ],
      "env": {
        "SGAI_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

这个服务器在你的电脑上运行，而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上，无需账户。

需要你填写的值

SGAI_API_KEY 机密 env
Your ScapeGraph API key (optional - can also be set via MCP config)

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。

它能做什么

它在你的电脑上运行；安装后，工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 ScrapeGraphAI 验证，该账户拥有此仓库
… 尚未检查
仍在维护
我们还没有从 GitHub 读取这个仓库
… 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
– 不适用
端点有响应
它在你的电脑上运行，没有互联网端点
– 不适用
使用 OAuth 登录
在你的电脑上运行，改用本地设置
… 尚未检查
工具描述中没有隐藏指令
它在你的电脑上运行；我们只能读取互联网端点的工具列表

与“网页与浏览器”中的其他服务器比较i

星标数多于此分类中其他 876 个服务器的 0%
发布到注册中心的时间比此分类中其他 876 个服务器的 2% 更新
基础检查结果等于或优于此分类中其他 876 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

常见问题

Scrapegraph MCP 安全吗？

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前，请先看看这个服务器要求哪些权限，并使用只具备所需权限的密钥。

它需要哪些密钥或代码？

你需要填写：SGAI_API_KEY

它在我的电脑上运行还是在云端？

它在你的电脑上运行。你的 AI 应用会在需要时启动它，数据不会经过作者的服务器（除非它自己调用在线服务）。

它还在维护吗？

GitHub 仓库最后更新于–，最新版本（1.0.1）于9个月前进入注册中心。

哪些应用可以使用它？

支持 MCP 的应用，例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它？

同一分类中有：Browser Use, Chrome DevTools MCP, MCP Server Browser

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Browser Use

作者：browser-use

Browser agents and stealth cloud browsers for AI: run web tasks, fill forms, extract data.

电脑或云端★ 120,087MIT16天前更新

安装

Chrome DevTools MCP

作者：ChromeDevTools

MCP server for Chrome DevTools

在你的电脑上运行★ 54,821Apache-2.015天前更新

安装

MCP Server Browser

作者：bytedance

MCP server for browser use access

在你的电脑上运行★ 39,550Apache-2.014个月前更新

安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

ScrapeGraph MCP Server

A production-ready Model Context Protocol (MCP) server that provides seamless integration with the ScrapeGraph AI API. This server enables language models to leverage advanced AI-powered web scraping capabilities with enterprise-grade reliability.

Key Features
Quick Start
Available Tools
Setup Instructions
Remote Server Usage
Local Usage
Google ADK Integration
Example Use Cases
Error Handling
Common Issues
Development
Contributing
Documentation
Technology Stack
License

API v2

This MCP server targets ScrapeGraph API v2 (https://v2-api.scrapegraphai.com/api), aligned 1:1 with scrapegraph-py PR #84. Auth uses the SGAI-APIKEY header. Environment variables mirror the Python SDK:

`SGAI_API_URL` — override the base URL (default https://v2-api.scrapegraphai.com/api)
`SGAI_TIMEOUT` — request timeout in seconds (default 120)
`SGAI_API_KEY` — API key (can also be passed via MCP scrapegraphApiKey or X-API-Key header)

Legacy aliases (still honored): SCRAPEGRAPH_API_BASE_URL for SGAI_API_URL, SGAI_TIMEOUT_S for SGAI_TIMEOUT.

Key Features

Scrape & extract: scrape (POST /scrape, multi-format), extract (POST /extract, URL + prompt)
Search: search (POST /search; num_results clamped 3–20)
Crawl: Async multi-page crawl with crawl_start / crawl_get_status / crawl_stop / crawl_resume
Schema: schema (POST /schema) — generate or augment a JSON Schema from a prompt
Monitors: Scheduled jobs via monitor_create, monitor_list, monitor_get, pause/resume/delete, monitor_activity (paginated tick history)
Account: credits, history
Easy integration: Claude Desktop, Cursor, Smithery, HTTP transport
Developer docs: .agent/ folder

Migration: v2 → v3

v3 renames every MCP tool that diverged from the v2 API docs. Hard rename, no aliases.

v2 (old)	v3 (new)
`smartscraper`	`extract`
`searchscraper`	`search`
`smartcrawler_initiate`	`crawl_start`
`smartcrawler_fetch_results`	`crawl_get_status`
`sgai_history`	`history`
`generate_schema`	`schema`
`markdownify`	removed — use `scrape` with `output_format="markdown"`

Quick Start

1. Get Your API Key

2. Install with Smithery (Recommended)

npx -y @smithery/cli install @ScrapeGraphAI/scrapegraph-mcp --client claude

3. Start Using

Ask Claude or Cursor:

"Convert https://scrapegraphai.com to markdown"
"Extract all product prices from this e-commerce page"
"Research the latest AI developments and summarize findings"

That's it! The server is now available to your AI assistant.

Available Tools

Tool	Role
`scrape`	POST /scrape (`output_format`: markdown, html, screenshot, branding, links, images, summary)
`extract`	POST /extract (requires `website_url` + `user_prompt`; optional `output_schema`)
`search`	POST /search (`num_results` 1–20; supports `country_search`, `time_range`, `output_schema`)
`crawl_start`	POST /crawl — `extraction_mode` markdown / html / links / images / summary / branding / screenshot
`crawl_get_status`	GET /crawl/:id (poll until `status: completed`)
`crawl_stop`, `crawl_resume`	POST /crawl/:id/stop \	resume
`schema`	POST /schema (generate or augment a JSON Schema from a prompt)
`credits`	GET /credits
`history`	GET /history (paginated, `service` filter)
`monitor_create`, `monitor_list`, `monitor_get`, `monitor_pause`, `monitor_resume`, `monitor_delete`	/monitor API
`monitor_activity`	GET /monitor/:id/activity (paginated tick history: `id`, `createdAt`, `status`, `changed`, `elapsedMs`, `diffs`)

Removed: sitemap, agentic_scrapper, async-status polling, and (in v3) markdownify — use scrape with output_format="markdown".

Setup Instructions

To utilize this server, you'll need a ScrapeGraph API key. Follow these steps to obtain one:

Navigate to the ScrapeGraph Dashboard
Create an account and generate your API key

Automated Installation via Smithery

For automated installation of the ScrapeGraph API Integration Server using Smithery:

npx -y @smithery/cli install @ScrapeGraphAI/scrapegraph-mcp --client claude

Claude Desktop Configuration

Update your Claude Desktop configuration file with the following settings (located on the top rigth of the Cursor page):

(remember to add your API key inside the config)

"mcpServers": { "@ScrapeGraphAI-scrapegraph-mcp": { "command": "npx", "args": [ "-y", "@smithery/cli@latest", "run", "@ScrapeGraphAI/scrapegraph-mcp", "--config", "\"{\\\"scrapegraphApiKey\\\":\\\"YOUR-SGAI-API-KEY\\\"}\"" ] } } }

The configuration file is located at:

Windows: %APPDATA%/Claude/claude_desktop_config.json
macOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json

Cursor Integration

Add the ScrapeGraphAI MCP server on the settings:

Remote Server Usage

Connect to our hosted MCP server - no local installation required!

[!WARNING]

The legacy MCP endpoint at https://mcp.scrapegraphai.com/mcp will be

deprecated soon. New integrations should use the replacement MCP endpoint:

https://sgai-mcp-main.onrender.com.

Claude Desktop Configuration (Remote)

Add this to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

"mcpServers": { "scrapegraph-mcp": { "command": "npx", "args": [ "mcp-remote@0.1.25", "https://sgai-mcp-main.onrender.com", "--header", "X-API-Key:YOUR_API_KEY" ] } } }

Cursor Configuration (Remote)

Cursor supports native HTTP MCP connections. Add to your Cursor MCP settings (~/.cursor/mcp.json):

"mcpServers": { "scrapegraph-mcp": { "url": "https://sgai-mcp-main.onrender.com", "headers": { "X-API-Key": "YOUR_API_KEY" } } } }

Benefits of Remote Server

No local setup - Just configure and start using
Always up-to-date - Automatically receives latest updates
Cross-platform - Works on any OS with Node.js

Local Usage

To run the MCP server locally for development or testing, follow these steps:

Prerequisites

Python 3.13 or higher
pip or uv package manager
ScrapeGraph API key

Installation

Clone the repository (if you haven't already):

git clone https://github.com/ScrapeGraphAI/scrapegraph-mcp

cd scrapegraph-mcp

Install the package:

# Using pip

pip install -e .

Or using uv (faster)

uv pip install -e .

Set your API key:

# macOS/Linux

export SGAI_API_KEY=your-api-key-here

Windows (PowerShell)

$env:SGAI_API_KEY="your-api-key-here"

Windows (CMD)

set SGAI_API_KEY=your-api-key-here

Running the Server Locally

You can run the server directly:

# Using the installed command

scrapegraph-mcp

Or using Python module

python -m scrapegraph_mcp.server

The server will start and communicate via stdio (standard input/output), which is the standard MCP transport method.

Testing with MCP Inspector

Test your local server using the MCP Inspector tool:

npx @modelcontextprotocol/inspector python -m scrapegraph_mcp.server

This provides a web interface to test all available tools interactively.

Configuring Claude Desktop for Local Server

To use your locally running server with Claude Desktop, update your configuration file:

macOS/Linux (~/Library/Application Support/Claude/claude_desktop_config.json):

"mcpServers": { "scrapegraph-mcp-local": { "command": "python", "args": [ "-m", "scrapegraph_mcp.server" ], "env": { "SGAI_API_KEY": "your-api-key-here" } } } }

Windows (%APPDATA%\Claude\claude_desktop_config.json):

"mcpServers": { "scrapegraph-mcp-local": { "command": "python", "args": [ "-m", "scrapegraph_mcp.server" ], "env": { "SGAI_API_KEY": "your-api-key-here" } } } }

Note: Make sure Python is in your PATH. You can verify by running python --version in your terminal.

Configuring Cursor for Local Server

In Cursor's MCP settings, add a new server with:

Command: python
Args: ["-m", "scrapegraph_mcp.server"]
Environment Variables: {"SGAI_API_KEY": "your-api-key-here"}

Troubleshooting Local Setup

Server not starting:

Verify Python is installed: python --version
Check that the package is installed: pip list | grep scrapegraph-mcp
Ensure API key is set: echo $SGAI_API_KEY (macOS/Linux) or echo %SGAI_API_KEY% (Windows)

Tools not appearing:

Check Claude Desktop logs:
macOS: ~/Library/Logs/Claude/
Windows: %APPDATA%\Claude\Logs\
Verify the server starts without errors when run directly
Check that the configuration JSON is valid

Import errors:

Reinstall the package: pip install -e . --force-reinstall
Verify dependencies: pip install -r requirements.txt (if available)

Google ADK Integration

The ScrapeGraph MCP server can be integrated with Google ADK (Agent Development Kit) to create AI agents with web scraping capabilities.

Prerequisites

Python 3.13 or higher
Google ADK installed
ScrapeGraph API key

Installation

Install Google ADK (if not already installed):

pip install google-adk

Set your API key:

export SGAI_API_KEY=your-api-key-here

Basic Integration Example

Create an agent file (e.g., agent.py) with the following configuration:

import os

from google.adk.agents import LlmAgent from google.adk.tools.mcp_tool.mcp_toolset import MCPToolset from google.adk.tools.mcp_tool.mcp_session_manager import StdioConnectionParams from mcp import StdioServerParameters

Path to the scrapegraph-mcp server directory

SCRAPEGRAPH_MCP_PATH = "/path/to/scrapegraph-mcp"

Path to the server.py file

SERVER_SCRIPT_PATH = os.path.join( SCRAPEGRAPH_MCP_PATH, "src", "scrapegraph_mcp", "server.py" )

root_agent = LlmAgent( model='gemini-2.0-flash', name='scrapegraph_assistant_agent', instruction='Help the user with web scraping and data extraction using ScrapeGraph AI. ' 'You can convert webpages to markdown, extract structur

只显示了开头部分；其余内容请在仓库中阅读

Scrapegraph MCP

概览

PopNx MCP 的三大支柱

它能帮你做什么

安装

安装之前

需要你填写的值

它能做什么

基础检查i

作者与仓库一致

仍在维护

有许可证

端点有响应

使用 OAuth 登录

工具描述中没有隐藏指令

与“网页与浏览器”中的其他服务器比较i

常见问题

替代选择

Browser Use

Chrome DevTools MCP

MCP Server Browser

作者的 README

ScrapeGraph MCP Server

Table of Contents

API v2

Key Features

Migration: v2 → v3

Quick Start

1. Get Your API Key

2. Install with Smithery (Recommended)

3. Start Using

Available Tools

Setup Instructions

Automated Installation via Smithery

Claude Desktop Configuration

Cursor Integration

Remote Server Usage

Claude Desktop Configuration (Remote)

Cursor Configuration (Remote)

Benefits of Remote Server

Local Usage

Prerequisites

Installation

Or using uv (faster)

Windows (PowerShell)

Windows (CMD)

Running the Server Locally

Or using Python module

Testing with MCP Inspector

Configuring Claude Desktop for Local Server

Configuring Cursor for Local Server

Troubleshooting Local Setup

Google ADK Integration

Prerequisites

Installation

Basic Integration Example

Path to the scrapegraph-mcp server directory

Path to the server.py file