MCP.so
登录

mcp-server-requests

@coucya

关于 mcp-server-requests

Web Content Retrieval (full webpage, filtered content, or Markdown-converted), Custom User-Agent, Multi-HTTP Method Support (GET/POST/PUT/DELETE/PATCH), LLM-Controlled Request Headers, LLM-Accessible Response Headers, and more.

基本信息

分类

AI 与智能体

许可证

MIT

运行时

python

传输方式

stdio

发布者

coucya

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-server-requests": {
      "command": "python",
      "args": [
        "-m",
        "mcp_server_requests"
      ]
    }
  }
}

工具

未检测到工具

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。

概览

What is mcp-server-requests?

An MCP server that provides HTTP request capabilities, enabling LLMs to fetch and process web content. It offers tools for fetching web content, saving it to files, and making generic HTTP requests, with support for content cleaning and markdown conversion.

How to use mcp-server-requests?

Install by cloning the repository and running pip install .. Configure in the MCP client settings by adding the command python -m mcp_server_requests to the mcpServers JSON. The server can also be started directly from the command line with various optional arguments for User‑Agent and root support.

Key features of mcp-server-requests

  • Fetch web content and convert to Markdown.
  • Filter out non‑visual elements (script, style, meta).
  • Save fetched content directly to files (avoids token consumption).
  • Generic HTTP requests with GET, POST, PUT, PATCH, DELETE.
  • Custom or random User‑Agent strings.
  • MCP workspace root support for file operations.

Use cases of mcp-server-requests

  • Fetch a web page and feed its Markdown content into an LLM.
  • Save scraped web content to a file for later analysis.
  • Make API calls with custom headers and body (JSON/text).
  • Retrieve raw HTML for processing outside the LLM context.
  • Use workspace roots to restrict file saving to project directories.

FAQ from mcp-server-requests

How do I install mcp-server-requests?

Clone the repository from GitHub, then run pip install . in the project directory. Python is required.

How can I customize the User-Agent?

Use the --user-agent flag with a custom string, or --random-user-agent to generate a random one optionally constrained by browser and OS.

What content cleaning options does the fetch tool provide

评论

AI 与智能体 分类下的更多 MCP 服务器