Enhanced Fetch MCP

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An AI-native web interaction layer that elevates Playwright into an intelligent, secure, and efficient service for AI agents.

Feature	Claude's Native Fetch	Standard Playwright	Enhanced Fetch MCP
Content Extraction	Basic	Manual Parsing	Advanced: Extracts main content, metadata, links, and images into clean Markdown.
JavaScript Rendering	❌ No	✅ Yes	✅ Yes: Full browser rendering for dynamic pages.
Security	✅ Safe	⚠️ Browser Sandbox	🔒 Maximum Security: All operations are isolated in a Docker container.
Resource Efficiency	High	Low	Hybrid Engine: Intelligently switches between lightweight HTTP and a full browser.
Screenshots & PDFs	❌ No	✅ Yes	✅ Yes: Captures screenshots and generates PDFs.
Control & Customization	Limited	High	Full Control: Customizable headers, timeouts, and more.

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Quick Start

Option 1: Local Installation

1. Install:

npm install -g enhanced-fetch-mcp

2. Configure Claude Code (~/.config/claude/config.json):

{
  "mcpServers": { "enhanced-fetch": { "command": "enhanced-fetch-mcp" } }
}

3. Use:

"Fetch the main content of https://example.com and take a screenshot."

Option 2: Install via Smithery

Alternatively, you can use Smithery to simplify the installation and configuration process.

Install via Smithery: https://smithery.ai/server/@Danielmelody/enhanced-fetch-mcp

Smithery automates the installation, dependency management, and MCP configuration for you. Important: The server runs entirely on your local machine—no data is sent to external servers. You maintain full control over your browsing activities, screenshots, and extracted content, ensuring maximum privacy and security.

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Tools

Web Scraping Tools (3)

Tool	Description
fetch_url	Makes a direct HTTP request to a URL to retrieve its raw HTML content. It supports various methods (GET, POST, etc.), custom headers, and other advanced options.
extract_content	Parses raw HTML to pull out structured information. It identifies the main article, cleans it, and returns it in multiple formats (text, Markdown, and HTML), along with metadata, links, and images.
fetch_and_extract	A convenient, all-in-one tool that first fetches a URL and then automatically extracts its content. It intelligently decides whether to use a simple HTTP request or a full browser.

Browser Automation Tools (8)

Tool	Description
create_browser_context	Initializes and launches a new, isolated browser instance (like Chrome, Firefox, or WebKit) with a clean session, returning a unique ID for future operations.
browser_navigate	Instructs a specific browser instance to visit a URL and waits for the page to load, including executing any initial JavaScript.
browser_get_content	Retrieves the full HTML of a page after it has been rendered by the browser, ensuring all dynamic content is present.
browser_screenshot	Captures a visual snapshot of the current page in the browser, which can be a full-page or a specific region, and returns the image data.
browser_pdf	Generates a PDF document from the current page's content, allowing for a printable, offline version of the web page.
browser_execute_js	Runs a custom JavaScript snippet within the context of the current page, enabling interaction with page elements or data retrieval.
list_browser_contexts	Returns a list of all currently active browser instances that have been created, along with their IDs and status.
close_browser_context	Terminates a browser instance and cleans up all associated resources, including closing all its pages and freeing up memory.

Docker Sandbox Tools (8)

Tool	Description
create_sandbox	Provisions a new, secure Docker container with a specified image, providing an isolated environment for command execution.
execute_in_sandbox	Runs a shell command inside a designated Docker sandbox and returns its standard output, error, and exit code.
list_sandboxes	Provides a list of all currently running Docker sandboxes, including their IDs, names, and current status.
get_sandbox	Retrieves detailed information about a specific sandbox, such as its configuration, running state, and network settings.
pause_sandbox	Temporarily freezes a running sandbox, preserving its state while consuming minimal CPU resources.
resume_sandbox	Unpauses a previously paused sandbox, allowing it to continue execution from where it left off.
cleanup_sandbox	Stops and completely removes a sandbox container, deleting its file system and freeing up all associated system resources.
get_sandbox_stats	Fetches real-time resource usage metrics for a sandbox, including CPU, memory, and network I/O.

Usage Examples

Simple Web Scraping

User: Fetch content from https://example.com

Claude automatically calls fetch_and_extract:
→ Fetch HTML
→ Extract title, description, body
→ Convert to Markdown
→ Return structured content

JavaScript-Rendered Pages

User: This page requires browser rendering

Claude automatically uses browser tools:
→ Create browser context
→ Navigate to page
→ Wait for JavaScript execution
→ Get fully rendered content

Web Screenshots

User: Take a screenshot of this page

Claude automatically calls browser screenshot:
→ Open page
→ Wait for loading completion
→ Capture full-page screenshot
→ Return PNG image

System Requirements

Required

• Node.js >= 18.0.0
• npm >= 8.0.0

Optional (for specific features)

• Docker (for sandbox functionality)
• Sufficient disk space (Playwright browsers ~300MB)

Verify Installation

# Check if command is available
enhanced-fetch-mcp --version
# Output: v1.0.0

# View help
enhanced-fetch-mcp --help

# Test run (Ctrl+C to exit)
enhanced-fetch-mcp
# Output: Enhanced Fetch MCP Server running on stdio

Troubleshooting

Command Not Found

# Check installation
npm list -g enhanced-fetch-mcp

# Reinstall
npm install -g enhanced-fetch-mcp

# Check path
which enhanced-fetch-mcp

Docker Not Running (affects sandbox functionality)

# macOS
open -a Docker

# Linux
sudo systemctl start docker

# Verify
docker ps

View Logs

# Server logs
tail -f ~/.local/share/enhanced-fetch-mcp/logs/browser-mcp.log

# Error logs
tail -f ~/.local/share/enhanced-fetch-mcp/logs/browser-mcp-error.log

Update

npm update -g enhanced-fetch-mcp

Development

Install from Source

# Clone project
git clone https://github.com/yourusername/enhanced-fetch-mcp.git
cd enhanced-fetch-mcp

# Install dependencies
npm install

# Build
npm run build

# Global link (development mode)
npm link

# Run tests
npm test

# Development mode (watch for changes)
npm run dev

Performance Metrics

Operation	Average Time
HTTP Request	200-300ms
Content Extraction	10-50ms
Browser Launch	300-500ms
Page Navigation	1.5-2s
Screenshot	~50ms
JavaScript Execution	<10ms

Contributing

Contributions are welcome! Please submit a Pull Request or create an Issue.

License

MIT License

Acknowledgments

• @modelcontextprotocol/sdk - MCP protocol implementation
• Playwright - Browser automation
• Cheerio - HTML parsing
• Turndown - HTML to Markdown conversion
• Dockerode - Docker API