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MCP-RQuest

MCP-RQuest

Public
xxxbrian/mcp-rquest

Advanced Model Context Protocol server offering realistic browser emulation with accurate TLS/JA3/JA4 fingerprints, full HTTP method support, secure request customization, and seamless PDF/HTML to Markdown conversion for enhanced large language model interactions.

python
0 tools
May 29, 2025
Updated Jun 4, 2025

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mcp-rquest

A Model Context Protocol (MCP) server that provides advanced HTTP request capabilities for Claude and other LLMs. Built on rquest, this server enables realistic browser emulation with accurate TLS/JA3/JA4 fingerprints, allowing models to interact with websites more naturally and bypass common anti-bot measures. It also supports converting PDF and HTML documents to Markdown for easier processing by LLMs.

Features

  • Complete HTTP Methods: Support for GET, POST, PUT, DELETE, PATCH, HEAD, OPTIONS, and TRACE
  • Browser Fingerprinting: Accurate TLS, JA3/JA4, and HTTP/2 browser fingerprints
  • Content Handling:
    • Automatic handling of large responses with token counting
    • HTML to Markdown conversion for better LLM processing
    • PDF to Markdown conversion using the Marker library
    • Secure storage of responses in system temporary directories
  • Authentication Support: Basic, Bearer, and custom authentication methods
  • Request Customization:
    • Headers, cookies, redirects
    • Form data, JSON payloads, multipart/form-data
    • Query parameters
  • SSL Security: Uses BoringSSL for secure connections with realistic browser fingerprints

Available Tools

  • HTTP Request Tools:

    • http_get - Perform GET requests with optional parameters
    • http_post - Submit data via POST requests
    • http_put - Update resources with PUT requests
    • http_delete - Remove resources with DELETE requests
    • http_patch - Partially update resources
    • http_head - Retrieve only headers from a resource
    • http_options - Retrieve options for a resource
    • http_trace - Diagnostic request tracing
  • Response Handling Tools:

    • get_stored_response - Retrieve stored large responses, optionally by line range
    • get_stored_response_with_markdown - Convert HTML or PDF responses to Markdown format for better LLM processing
    • get_model_state - Get the current state of the PDF models loading process
    • restart_model_loading - Restart the PDF models loading process if it failed or got stuck

PDF Support

mcp-rquest now supports PDF to Markdown conversion, allowing you to download PDF files and convert them to Markdown format that's easy for LLMs to process:

  1. Automatic PDF Detection: PDF files are automatically detected based on content type
  2. Seamless Conversion: The same get_stored_response_with_markdown tool works for both HTML and PDF files
  3. High-Quality Conversion: Uses the Marker library for accurate PDF to Markdown transformation
  4. Optimized Performance: Models are pre-downloaded during package installation to avoid delays during request processing

Installation

Using uv (recommended)

When using uv no specific installation is needed. We will use uvx to directly run mcp-rquest.

Using pip

Alternatively you can install mcp-rquest via pip:

pip install mcp-rquest

After installation, you can run it as a script using:

python -m mcp_rquest

Configuration

Configure for Claude.app

Add to your Claude settings:

Using uvx:

{ "mcpServers": { "http-rquest": { "command": "uvx", "args": ["mcp-rquest"] } } }

Using pip:

{ "mcpServers": { "http-rquest": { "command": "python", "args": ["-m", "mcp_rquest"] } } }

Using pipx:

{ "mcpServers": { "http-rquest": { "command": "pipx", "args": ["run", "mcp-rquest"] } } }

Browser Emulation

mcp-rquest leverages rquest's powerful browser emulation capabilities to provide realistic browser fingerprints, which helps bypass bot detection and access content normally available only to standard browsers. Supported browser fingerprints include:

  • Chrome (multiple versions)
  • Firefox
  • Safari (including iOS and iPad versions)
  • Edge
  • OkHttp

This ensures that requests sent through mcp-rquest appear as legitimate browser traffic rather than bot requests.

Development

Setting up a Development Environment

  1. Clone the repository
  2. Create a virtual environment using uv:
    uv venv
  3. Activate the virtual environment:
    # Unix/macOS source .venv/bin/activate # Windows .venv\Scripts\activate
  4. Install development dependencies:
    uv pip install -e ".[dev]"

Acknowledgements

  • This project is built on top of rquest, which provides the advanced HTTP client with browser fingerprinting capabilities.
  • rquest is based on a fork of reqwest.
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