@simonediroma
基本信息
暂无概览
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"webfetch": {
"command": "/absolute/path/to/.venv/bin/python",
"args": [
"/absolute/path/to/server.py"
],
"env": {
"WEBFETCH_CONFIG": "/absolute/path/to/webfetch.yaml"
}
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
webfetch-mcp is a local Python MCP server that replaces an AI assistant’s built-in WebFetch tool with a fully configurable HTTP client. It supports domain-scoped headers, retries, proxies, timeouts, output formats, bot-block detection, and prompt-injection sanitization.
Clone the repository, create a Python 3.10+ virtual environment, install dependencies from requirements.txt, copy and edit the YAML configuration file (webfetch.yaml.example → webfetch.yaml), then register the server’s command, args, and env in your AI assistant’s MCP server settings (e.g., ~/.claude/settings.json). Restart the assistant; the tool is exposed as mcp__webfetch__fetch.
trafilatura format.The built-in tool sends requests without custom headers, so it is blocked by bot-protection systems and cannot authenticate against APIs. webfetch-mcp allows per-domain headers, retries, proxies, and output formatting, all configured automatically.
Python 3.10+ and the packages in `requirements.txt`: `mcp[cli]`, `httpx`, `python-dotenv`, `markdownify`, `trafilatura`, `pyyaml`, and `beautifulsoup4`. JS rendering requires Playwright (`playwright install chromium`).
The server fetches data directly and returns it to the AI assistant in the response. No data is stored or persisted by the server itself. Response length can be capped with `max_bytes`.
It communicates with MCP-compatible assistants over stdio (the command-line invocation). Authentication is handled by domain-scoped headers set in the YAML config file.
The README does not document explicit functional limits. It supports response truncation via `max_bytes` to avoid filling the assistant’s context window.
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