mcp-server-requests
@coucya
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.
Basic information
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-server-requests": {
"command": "python",
"args": [
"-m",
"mcp_server_requests"
]
}
}
}Tools
No tools detected
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.
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
More AI & Agents MCP servers
MCP Client for Ollama (ollmcp)
joniglHarness the power of local LLMs with this TUI MCP Client for Ollama. Featuring all core MCP primitives (tools, prompts, resources), agent mode, multi-server, model switching, streaming responses, human-in-the-loop, thinking mode, model params config, system prompts, and saved pre
Shell and Coding agent for Claude and other mcp clients
rusiaamanShell and coding agent on mcp clients
MCP-NixOS - Because Your AI Assistant Shouldn't Hallucinate About Packages
utensilsMCP-NixOS - Model Context Protocol Server for NixOS resources
Perplexity Ask MCP Server
ppl-aiThe official MCP server implementation for the Perplexity API Platform
meGPT - upload an author's content into an LLM
adriancoCode to process many kinds of content by an author into an MCP server
Comments