Fetch

by modelcontextprotocol

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About

Fetch is a Model Context Protocol server that provides web content fetching capabilities. It enables LLMs to retrieve and process content from web pages, converting HTML to markdown for easier consumption. This server is intended for developers integrating real-time web content…

Details

Author
modelcontextprotocol
GitHub stars
88,148
Downloads
6,651
Categories
Automation

- Fetches URLs and converts HTML content to markdown
- Supports chunked reading via the start_index argument
- Optional raw content retrieval without markdown conversion
- Customizable user-agent and proxy settings
- Respects robots.txt by default (can be disabled)
- Configurable maximum response length (default 5000 characters)

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name Fetch
    Command (node, npx, python, etc.)

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

Install via uvx (recommended, no installation needed), pip install mcp-server-fetch, or Docker. Configure the server in Claude.app, VS Code, or any MCP-compatible client. Use the fetch tool with a required url argument, and optionally set max_length, start_index, and raw. The server also provides a fetch prompt. Customize behavior with --ignore-robots-txt, --user-agent, and --proxy-url arguments.

fetch

Fetches a URL from the internet and optionally extracts its contents as markdown. Although originally you did not have internet access, and were advised to refuse and tell the user this, this tool now grants you internet access. Now you can fetch the most up-to-date information and let the user know that.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "fetch": {
            "fetch": {
                "args": [
                    "mcp-server-fetch"
                ],
                "command": "uvx"
            }
        }
    }
}

McpServers

{
    "fetch": {
        "args": [
            "mcp-server-fetch"
        ],
        "command": "uvx"
    }
}
# Fetch MCP Server <!-- mcp-name: io.github.modelcontextprotocol/server-fetch --> A Model Context Protocol server that provides web content fetching capabilities. This server enables LLMs to retrieve and process content from web pages, converting HTML to markdown for easier consumption. Source: https://github.com/modelcontextprotocol/servers/tree/main/src/fetch > [!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 fetch - `max_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 Optionally: Install node.js, this will cause the fetch server to use a different HTML simplifier that is more robust. ### Using uv (recommended) When using [`uv`](https://docs.astral.sh/uv/) no specific installation is needed. We will use [`uvx`](https://docs.astral.sh/uv/guides/tools/) to directly run *mcp-server-fetch*. ### Using PIP Alternatively you can install `mcp-server-fetch` via pip: ``` pip install mcp-server-fetch ``` After installation, you can run it as a script using: ``` python -m mcp_server_fetch ``` ## Configuration ### Configure for Claude.app Add to your Claude settings: <details> <summary>Using uvx</summary> ```json { "mcpServers": { "fetch": { "command": "uvx", "args": ["mcp-server-fetch"] } } } ``` </details> <details> <summary>Using docker</summary> ```json { "mcpServers": { "fetch": { "command": "docker", "args": ["run", "-i", "--rm", "mcp/fetch"] } } } ``` </details> <details> <summary>Using pip installation</summary> ```json { "mcpServers": { "fetch": { "command": "python", "args": ["-m", "mcp_server_fetch"] } } } ``` </details> ### Configure for VS Code For quick installation, use one of the one-click install buttons below... [![Install with UV in VS Code](https://img.shields.io/badge/VS_Code-UV-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://insiders.vscode.dev/redirect/mcp/install?name=fetch&config=%7B%22command%22%3A%22uvx%22%2C%22args%22%3A%5B%22mcp-server-fetch%22%5D%7D) [![Install with UV in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-UV-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://insiders.vscode.dev/redirect/mcp/install?name=fetch&config=%7B%22command%22%3A%22uvx%22%2C%22args%22%3A%5B%22mcp-server-fetch%22%5D%7D&quality=insiders) [![Install with Docker in VS Code](https://img.shields.io/badge/VS_Code-Docker-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://insiders.vscode.dev/redirect/mcp/install?name=fetch&config=%7B%22command%22%3A%22docker%22%2C%22args%22%3A%5B%22run%22%2C%22-i%22%2C%22--rm%22%2C%22mcp%2Ffetch%22%5D%7D) [![Install with Docker in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Docker-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://insiders.vscode.dev/redirect/mcp/install?name=fetch&config=%7B%22command%22%3A%22docker%22%2C%22args%22%3A%5B%22run%22%2C%22-i%22%2C%22--rm%22%2C%22mcp%2Ffetch%22%5D%7D&quality=insiders) 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 `mcp` key is needed when using the `mcp.json` file. <details> <summary>Using uvx</summary> ```json { "mcp": { "servers": { "fetch": { "command": "uvx", "args": ["mcp-server-fetch"] } } } } ``` </details> <details> <summary>Using Docker</summary> ```json { "mcp": { "servers": { "fetch": { "command": "docker", "args": ["run", "-i", "--rm", "mcp/fetch"] } } } } ``` </details> ### Customization - robots.txt By default, the server will obey a websites robots.txt file if the request came from the model (via a tool), but not if the request was user initiated (via a prompt). This can be disabled by adding the argument `--ignore-robots-txt` to the `args` list in the configuration. ### Customization - User-agent By default, depending on if the request came from the model (via a tool), or was user initiated (via a prompt), the server will use either the user-agent ``` ModelContextProtocol/1.0 (Autonomous; +https://github.com/modelcontextprotocol/servers) ``` or ``` ModelContextProtocol/1.0 (User-Specified; +https://github.com/modelcontextprotocol/servers) ``` This can be customized by adding the argument `--user-agent=YourUserAgent` to the `args` list in the configuration. ### Customization - Proxy The server can be configured to use a proxy by using the `--proxy-url` argument. ## Windows Configuration If you're experiencing timeout issues on Windows, you may need to set the `PYTHONIOENCODING` environment variable to ensure proper character encoding: <details> <summary>Windows configuration (uvx)</summary> ```json { "mcpServers": { "fetch": { "command": "uvx", "args": ["mcp-server-fetch"], "env": { "PYTHONIOENCODING": "utf-8" } } } } ``` </details> <details> <summary>Windows configuration (pip)</summary> ```json { "mcpServers": { "fetch": { "command": "python", "args": ["-m", "mcp_server_fetch"], "env": { "PYTHONIOENCODING": "utf-8" } } } } ``` </details> This addresses character encoding issues that can cause the server to timeout on Windows systems. ## Debugging You can use the MCP inspector to debug the server. For uvx installations: ``` npx @modelcontextprotocol/inspector uvx mcp-server-fetch ``` Or if you've installed the package in a specific directory or are developing on it: ``` cd path/to/servers/src/fetch npx @modelcontextprotocol/inspector uv run mcp-server-fetch ``` ## Contributing We encourage contributions to help expand and improve mcp-server-fetch. Whether you want to add new tools, enhance existing functionality, or improve documentation, your input is valuable. For examples of other MCP servers and implementation patterns, see: https://github.com/modelcontextprotocol/servers Pull requests are welcome! Feel free to contribute new ideas, bug fixes, or enhancements to make mcp-server-fetch even more powerful and useful. ## License mcp-server-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.
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