How do I install mcp-server-requests?
Clone the repository from GitHub, then run `pip install .` in the project directory. Python is required.
MCP Server Requests
@coucya
Basic information
About 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.
MCP Server Requests config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-server-requests": {
"command": "python",
"args": [
"-m",
"mcp_server_requests"
]
}
}
}MCP Server Requests tools
Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
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.
Frequently asked questions
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.
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