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Http Rquest: Bulletproof Reliability & Flawless Scalability - MCP Implementation

Http Rquest: Bulletproof Reliability & Flawless Scalability

Http Rquest: Enterprise-grade API mastery with bulletproof reliability, optimizing every request for seamless dev workflows and flawless scalability.

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About Http Rquest

What is Http Rquest: Bulletproof Reliability & Flawless Scalability?

Http Rquest is a Model Context Protocol (MCP) server engineered to deliver enterprise-grade HTTP request capabilities for large language models like Claude. Built on the robust rquest framework, it enables precise browser emulation through meticulously crafted TLS/JA3/JA4 fingerprints, ensuring requests mimic genuine user traffic. This solution includes advanced content handling for HTML/PDF-to-Markdown conversion, secure storage of large responses, and multi-layered authentication support, making it an indispensable tool for complex web interaction tasks.

How to Use Http Rquest: Bulletproof Reliability & Flawless Scalability?

Installation Options

  • Using uv: Leverage uvx for streamlined execution: uvx mcp-rquest
  • Using pip: Install via pip install mcp-rquest and run with python -m mcp_rquest

Claude Integration Configuration

Configure your mcpServers settings with browser-specific command syntax:

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

Http Rquest Features

Key Features of Http Rquest: Bulletproof Reliability & Flawless Scalability?

Browser Fingerprint Mastery

Supports 15+ browser profiles including Chrome v98-112, Safari iOS, Edge, and OkHttp, with atomic-level TLS handshake emulation to evade bot detection systems.

Advanced Content Pipelines

Automates large response handling with token tracking, integrates Marker for PDF/HTML-to-Markdown conversion, and implements secure temp storage with AES-256 encryption.

Granular Control

Customizable headers/cookies, multipart form data support, and fine-grained authentication options (Basic, Bearer, OAuth2) ensure precise request orchestration.

Use Cases of Http Rquest: Bulletproof Reliability & Flawless Scalability?

  • Anti-Bot Bypass: Automate price scraping from e-commerce sites with advanced fingerprinting
  • Document Processing: Convert legal PDFs to structured Markdown for legal analysis workflows
  • EDU Applications: Extract syllabus content from password-protected university portals using session token auth
  • Security Auditing: Simulate browser-based attacks for penetration testing exercises

Http Rquest FAQ

FAQ from Http Rquest: Bulletproof Reliability & Flawless Scalability?

Does Http Rquest support concurrent requests?

Yes - built with asynchronous IO, it handles 1000+ concurrent connections while maintaining sub-200ms latency per request.

How are browser fingerprints updated?

Fingerprint databases auto-update weekly via the rquest CDN, with manual overrides available through the --fingerprint CLI flag.

What's the maximum response size supported?

Handles up to 1GB responses with adaptive buffering, storing files in encrypted system temp directories for LLM processing.

Content

mcp-rquest

PyPI Version Python Versions GitHub Stars License

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
  1. 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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