Fetch MCP Server
Enables LLMs to fetch and extract web content as markdown with browser impersonation to bypass basic bot detection.
README
Fetch MCP Server (Browser Impersonation Fork)
A Model Context Protocol server that provides web content fetching capabilities with browser impersonation. This server enables LLMs to retrieve and process content from web pages, converting HTML to markdown for easier consumption.
This is a fork of the original MCP fetch server that utilizes curl_cffi for browser impersonation, allowing it to bypass basic bot detection and access websites that might block standard HTTP requests.
Key Features
- Browser Impersonation: Uses curl_cffi to mimic real browser requests, helping bypass basic bot detection
- Content Extraction: Converts HTML to markdown for easier LLM consumption
- Chunked Reading: Support for reading large webpages in chunks using
start_index - Browser Headers: Uses realistic Chrome browser headers for better compatibility
[!CAUTION] This server can access local/internal IP addresses and may represent a security risk. Exercise caution when using this MCP server to ensure this does not expose any sensitive data.
The fetch tool will truncate the response, but by using the start_index argument, you can specify where to start the content extraction. This lets models read a webpage in chunks, until they find the information they need.
Available Tools
fetch- Fetches a URL from the internet and extracts its contents as markdown.url(string, required): URL to fetchmax_length(integer, optional): Maximum number of characters to return (default: 5000)start_index(integer, optional): Start content from this character index (default: 0)raw(boolean, optional): Get raw content without markdown conversion (default: false)
Prompts
- fetch
- Fetch a URL and extract its contents as markdown
- Arguments:
url(string, required): URL to fetch
Installation
Using uv
When using uv no specific installation is needed. We will
use uvx to directly run from the git repository:
uvx --from git+https://github.com/evanlouie/mcp-fetch.git mcp-server-fetch
Configuration
Configure for Claude.app
Add to your Claude settings:
{
"mcpServers": {
"fetch": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/evanlouie/mcp-fetch.git",
"mcp-server-fetch"
],
"env": {
"PYTHONWARNINGS": "ignore",
"npm_config_audit": "false",
"npm_config_fund": "false"
}
}
}
}
Configure for VS Code
For manual installation, 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).
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.
Note that the
mcpkey is needed when using themcp.jsonfile.
{
"mcp": {
"servers": {
"fetch": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/evanlouie/mcp-fetch.git",
"mcp-server-fetch"
],
"env": {
"PYTHONWARNINGS": "ignore",
"npm_config_audit": "false",
"npm_config_fund": "false"
}
}
}
}
}
Customization - Proxy
The server can be configured to use a proxy by using the --proxy-url argument.
Troubleshooting
JSON Parsing Errors
If you encounter JSON parsing errors like:
Unexpected token 'o', "found 0 vul"... is not valid JSON
This is caused by security scanners or audit tools outputting non-JSON content to stdout during package installation. The MCP protocol requires pure JSON-RPC messages on stdout, but vulnerability scanners (like npm audit) can contaminate this output.
Solution: The environment variables in the configuration examples above suppress these outputs:
PYTHONWARNINGS=ignore- Suppresses Python warning messagesnpm_config_audit=false- Disables npm security auditsnpm_config_fund=false- Disables npm funding messages
Alternative Solution: If you continue to experience issues, you can create a wrapper script:
#!/bin/bash
uvx --from git+https://github.com/evanlouie/mcp-fetch.git mcp-server-fetch 2>/dev/null
Then use the wrapper script path as your command instead of uvx.
Debugging
You can use the MCP inspector to debug the server. For uvx installations:
npx @modelcontextprotocol/inspector uvx --from git+https://github.com/evanlouie/mcp-fetch.git mcp-server-fetch
Or if you've installed the package in a specific directory or are developing on it:
cd path/to/mcp-fetch
npx @modelcontextprotocol/inspector uv run src/mcp_fetch
Contributing
We encourage contributions to help expand and improve mcp-fetch. Whether you want to add new tools, enhance existing functionality, or improve documentation, your input is valuable.
This project is a fork of the original MCP fetch server. For the original implementation and other MCP servers, see: https://github.com/modelcontextprotocol/servers
Pull requests are welcome! Feel free to contribute new ideas, bug fixes, or enhancements to make mcp-fetch even more powerful and useful.
Acknowledgments
This project is based on the original MCP fetch server from the Model Context Protocol team. The browser impersonation capabilities are powered by curl_cffi.
License
mcp-fetch is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.