a","10",{"property":"og:image:width","content":"1200"}],["$","meta","11",{"property":"og:image:height","content":"630"}],["$","meta","12",{"property":"og:type","content":"website"}],["$","meta","13",{"name":"twitter:card","content":"summary"}],["$","meta","14",{"name":"twitter:site","content":"MCP.so"}],["$","meta","15",{"name":"twitter:title","content":"MCPサーバー"}],["$","meta","16",{"name":"twitter:description","content":"素晴らしいMCPサーバーやClaude MCP統合を含む、最大のMCPサーバーコレクション。AIの能力を向上させるMCPサーバーを検索して発見しましょう。"}],["$","meta","17",{"name":"twitter:image","content":"https://mcp.so/logo.png"}]],"error":null,"digest":"$undefined"} e:{"metadata":"$14:metadata","error":null,"digest":"$undefined"} 29:T1048,# Fetch MCP Server 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. 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:

Using uvx

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

Using docker

```json "mcpServers": { "fetch": { "command": "docker", "args": ["run", "-i", "--rm", "mcp/fetch"] } } ```

Using pip installation

```json "mcpServers": { "fetch": { "command": "python", "args": ["-m", "mcp_server_fetch"] } } ```

### 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. ## 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 spe

Fetch

ツール

fetch

サーバー設定