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Fetch Browser
What is Fetch Browser
Fetch-Browser is a powerful headless browser MCP server that allows AI agents to fetch web content and perform Google searches without the need for API keys. It is built with modern web standards for seamless integration with AI platforms.
Use cases
Use cases for Fetch-Browser include automating web content retrieval for AI applications, performing structured Google searches for data extraction, and converting web content into various formats for further processing.
How to use
To use Fetch-Browser, install it via Smithery CLI or manually by cloning the repository and running the server. You can execute Google searches or fetch content from any URL using the provided tools, specifying the desired response format.
Key features
Key features include no API keys required, smart Google search capabilities, universal content fetching from any webpage or API endpoint, multiple output formats (HTML, JSON, Text, Markdown), automatic content type detection, and robust error handling.
Where to use
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Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Fetch Browser
Fetch-Browser is a powerful headless browser MCP server that allows AI agents to fetch web content and perform Google searches without the need for API keys. It is built with modern web standards for seamless integration with AI platforms.
Use cases
Use cases for Fetch-Browser include automating web content retrieval for AI applications, performing structured Google searches for data extraction, and converting web content into various formats for further processing.
How to use
To use Fetch-Browser, install it via Smithery CLI or manually by cloning the repository and running the server. You can execute Google searches or fetch content from any URL using the provided tools, specifying the desired response format.
Key features
Key features include no API keys required, smart Google search capabilities, universal content fetching from any webpage or API endpoint, multiple output formats (HTML, JSON, Text, Markdown), automatic content type detection, and robust error handling.
Where to use
undefined
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
Fetch Browser
A powerful headless browser MCP server that enables AI agents to fetch web content and perform Google searches without requiring any API keys. Built with modern web standards and designed for seamless integration with AI platforms.
Features
-
No API Keys Required: Uses a sophisticated headless browser approach to fetch content directly
-
Smart Google Search:
- Extract structured results from Google searches
- Support for both web and news results
- Configurable number of results (1-100)
- Full content fetching of search results
- Automatic retry and error handling
-
Universal Content Fetching:
- Support for any webpage or API endpoint
- Multiple output formats (HTML, JSON, Text, Markdown)
- Automatic content type detection
- Response size limits and timeout protection
- Rate limiting protection
-
Format Conversion:
- Clean HTML to Markdown conversion
- Pretty-printed JSON responses
- Structured HTML output
- Plain text with proper formatting
Tools
1. Google Search Tool (google_search)
Executes Google searches and fetches full content of results:
{
query: "your search query",
responseType: "markdown", // or "json", "html", "text"
maxResults: 10, // 1-100 results
topic: "web" // or "news"
}
2. URL Fetcher Tool (fetch_url)
Fetches content from any URL:
{
url: "https://example.com",
responseType: "markdown", // or "json", "html", "text"
timeout: 30000 // optional, in milliseconds
}
Installation
Via Smithery
# For Claude
npx -y @smithery/cli install @TheSethRose/fetch-browser --client claude
# For Cursor
npx -y @smithery/cli install @TheSethRose/fetch-browser --client cursor
# For TypeScript
npx -y @smithery/cli install @TheSethRose/fetch-browser --client typescript
Manual Installation
# Clone the repository
git clone https://github.com/TheSethRose/fetch-browser.git
cd fetch-browser
# Install dependencies
npm install
# Build the project
npm run build
# Start the server
npm start
Development
# Watch mode with auto-rebuild
npm run watch
# Run with inspector
npm run inspector
# Debug mode
npm run debug
# Debug with watch mode
npm run debug:watch
Response Formats
1. Markdown Format
## [Page Title](https://example.com)
Content converted to clean markdown with:
- Lists
- **Bold text**
- *Italic text*
- [Links](https://example.com)
2. JSON Format
{
"url": "https://example.com",
"content": "Extracted content...",
"error": null
}
3. HTML Format
<div class="search-result">
<h2><a href="https://example.com">Page Title</a></h2>
<div class="content">
Original HTML content
</div>
</div>
4. Text Format
### https://example.com Plain text content with preserved formatting ==========
Error Handling
- Automatic retries with exponential backoff
- Rate limiting protection
- Timeout handling
- Detailed error messages
- Individual result error tracking
Security Features
- Response size limits
- Request timeouts
- Rate limiting protection
- No API keys or secrets required
- Proper error handling
Credits
Created by Seth Rose:
- Website: https://www.sethrose.dev
- 𝕏 (Twitter): https://x.com/TheSethRose
- 🦋 (Bluesky): https://bsky.app/profile/sethrose.dev
License
MIT License - See LICENSE for details
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.










