Skip to main 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

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.

Metadata

Release files for mcp-rquest 0.1.13

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for mcp-rquest 0.1.13
File Size Uploaded
mcp_rquest-0.1.13.tar.gz 121.2 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for mcp-rquest 0.1.13
File Interpreter ABI Platform
mcp_rquest-0.1.13-py3-none-any.whl Python 3 none any Details

Total release size: 132.6 kB

Release files / mcp_rquest-0.1.13.tar.gz

Download URL mcp_rquest-0.1.13.tar.gz
Size 121.2 kB
Tags Source
SHA-256 checksum
How to use checksums
7b4c2c1a7ef167c0a35550d1b1deda7d72e088d9ffe91d8421b1bfbc514053e3
BLAKE2b-256 checksum
How to use checksums
c749c79a7d9284b6414f4df6037598672fc2eced2ddd76729ceec1cf91dd15fc
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.10.14

Release files / mcp_rquest-0.1.13-py3-none-any.whl

Download URL mcp_rquest-0.1.13-py3-none-any.whl
Size 11.4 kB
Tags Python 3
SHA-256 checksum
How to use checksums
10e5743f36728ce1e3b10752c6394359b620e4cc71c15f27cd03394a483817aa
BLAKE2b-256 checksum
How to use checksums
1dd29d7a26e051c3c005471e954d0582b4021a05f32afd1550e5a07dd65b8186
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.10.14

Release history Release notifications | RSS feed

This release

0.1.13 This release

2 release files

0.1.12

2 release files

0.1.11

2 release files

0.1.10

2 release files

0.1.9

2 release files

0.1.8

2 release files

0.1.7

2 release files

0.1.6

2 release files

0.1.5

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page