// may the 4th be with you⚔️
browser-automationsearch-web

HTTP Request

by xxxbrian

Advanced web scraper lets LLMs bypass anti-bot protection using HTTP requests, ideal for web scraping tools like Octopar

Enables LLMs to make advanced HTTP requests with realistic browser emulation, bypassing anti-bot measures while supporting all HTTP methods, authentication, and automatic response handling for web scraping and API interactions.

github stars

43

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Realistic browser fingerprintsAnti-bot bypass capabilitiesAutomatic content-to-Markdown conversion

best for

  • / Web scraping protected sites
  • / API testing and interaction
  • / Content extraction for LLM analysis
  • / Automating web data collection

capabilities

  • / Make HTTP requests with browser fingerprinting
  • / Convert HTML and PDF content to Markdown
  • / Handle authentication (Basic, Bearer, custom)
  • / Bypass anti-bot detection systems
  • / Process large responses with token counting
  • / Support all HTTP methods (GET, POST, PUT, DELETE, etc.)

what it does

Makes HTTP requests with realistic browser emulation to bypass anti-bot measures and convert web content to Markdown for LLM processing.

about

HTTP Request is a community-built MCP server published by xxxbrian that provides AI assistants with tools and capabilities via the Model Context Protocol. Advanced web scraper lets LLMs bypass anti-bot protection using HTTP requests, ideal for web scraping tools like Octopar It is categorized under browser automation, search web.

how to install

You can install HTTP Request in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

HTTP Request is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

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"]
    }
  }
}
</details>

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.

FAQ

What is the HTTP Request MCP server?
HTTP Request is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for HTTP Request?
This profile displays 69 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.8 out of 5—verify behavior in your own environment before production use.

Discussion

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MCP server reviews

Ratings

4.869 reviews
  • Layla Desai· Dec 28, 2024

    HTTP Request is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Ira Kim· Dec 24, 2024

    According to our notes, HTTP Request benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Maya Lopez· Dec 16, 2024

    We evaluated HTTP Request against two servers with overlapping tools; this profile had the clearer scope statement.

  • Ira Verma· Dec 12, 2024

    HTTP Request has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Zaid Brown· Dec 12, 2024

    We evaluated HTTP Request against two servers with overlapping tools; this profile had the clearer scope statement.

  • Ira Huang· Dec 12, 2024

    We wired HTTP Request into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Isabella Abebe· Dec 8, 2024

    HTTP Request is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Lucas Bhatia· Dec 4, 2024

    According to our notes, HTTP Request benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Lucas Robinson· Nov 27, 2024

    HTTP Request has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Zaid Patel· Nov 23, 2024

    We wired HTTP Request into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

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