Wireshark MCP (Model Context Protocol)

A Model Context Protocol (MCP) server for integrating Wireshark network analysis capabilities with AI systems like Claude. This implementation provides direct integration with Claude without requiring manual copy/paste of prompts.

What is Wireshark MCP?

Wireshark MCP provides a standardized way for AI assistants to access and analyze network packet data through Wireshark. It bridges the gap between low-level network data and high-level AI understanding by implementing the Model Context Protocol.

<p align="center"> <img src="https://raw.githubusercontent.com/sarthaksiddha/Wireshark-mcp/main/docs/images/wireshark-mcp-flow.png" alt="Wireshark MCP Flow" width="600"/> </p>

The server provides tools for:

1. Capturing live network traffic
2. Analyzing existing pcap files
3. Extracting protocol-specific information
4. Summarizing network flows

Quick Start

Installation

# Clone the repository 
git clone https://github.com/sarthaksiddha/Wireshark-mcp.git 
cd Wireshark-mcp

# Install dependencies
pip install -e .

Running the MCP Server

# Run with stdio transport (for Claude Desktop)
python mcp_server.py --stdio

# Run with SSE transport (for other MCP clients)
python mcp_server.py --host 127.0.0.1 --port 5000

Configuring Claude Desktop

To configure Claude Desktop to use the Wireshark MCP server:

1. Open Claude Desktop
2. Go to Settings > Developer > Edit Config
3. Add the following configuration:

{
  "mcpServers": {
    "wireshark": {
      "command": "python",
      "args": [
        "/path/to/wireshark-mcp/mcp_server.py",
        "--stdio"
      ]
    }
  }
}

Replace /path/to/wireshark-mcp with the actual path to your repository.

Available Tools

The Wireshark MCP server provides the following tools:

• capture_live_traffic: Capture live network traffic using tshark
• analyze_pcap: Analyze an existing pcap file
• get_protocol_list: Get a list of supported protocols

Example Usage in Claude

Once configured, you can use the Wireshark MCP server in Claude with queries like:

• "Capture 30 seconds of network traffic on my system and show me what's happening"
• "Analyze my network.pcap file and tell me if there are any suspicious activities"
• "What protocols can I focus on when analyzing network traffic?"

Key Features

• Packet Summarization: Convert large pcap files into token-optimized summaries
• Protocol Intelligence: Enhanced context for common protocols (HTTP, DNS, TLS, SMTP, etc.)
• Flow Tracking: Group related packets into conversation flows
• Anomaly Highlighting: Emphasize unusual or suspicious patterns
• Query Templates: Pre-built prompts for common network analysis tasks
• Visualization Generation: Create text-based representations of network patterns
• Multi-level Abstraction: View data from raw bytes to high-level behaviors
• Web Interface: Browser-based UI for easier analysis and visualization
• Agent-to-Agent (A2A) Integration: Expose packet analysis as an A2A-compatible agent
• Advanced Security Framework: Comprehensive security controls for data protection and communication
• IP Address Protection: Multiple strategies for anonymizing sensitive network addresses
• Secure Communication: Robust message signatures for secure agent-to-agent communication
• Cross-Platform: Works on Windows, macOS, and Linux

Documentation

• Claude Integration Guide - Detailed guide for connecting with Claude AI
• A2A Module Documentation - Guide for using the Agent-to-Agent integration
• A2A Security Guide - Security considerations for A2A integration
• IP Protection Guide - Detailed guide on IP address anonymization and obfuscation
• Security Manager Guide - Comprehensive guide to the unified security framework
• Message Security Signatures - Guide for secure message signing and verification
• Web Interface README - Information on using the web interface
• Utility Scripts - Helpful scripts for PCAP analysis

Basic Usage

from wireshark_mcp import WiresharkMCP, Protocol
from wireshark_mcp.formatters import ClaudeFormatter

# Initialize with a pcap file
mcp = WiresharkMCP("capture.pcap")

# Generate a basic packet summary
context = mcp.generate_context(
    max_packets=100,
    focus_protocols=[Protocol.HTTP, Protocol.DNS],
    include_statistics=True
)

# Format it for Claude
formatter = ClaudeFormatter()
claude_prompt = formatter.format_context(
    context, 
    query="What unusual patterns do you see in this HTTP traffic?"
)

# Save to file for use with Claude
with open("claude_prompt.md", "w") as f:
    f.write(claude_prompt)

Using with Claude

There are three main ways to use Wireshark MCP with Claude:

1. Direct MCP Integration (NEW)

For seamless integration with Claude Desktop:

# Run the MCP server with stdio transport
python mcp_server.py --stdio

Then configure Claude Desktop as described in the "Configuring Claude Desktop" section above. This method provides direct integration without any copy/paste needed.

2. Simple Script Approach

For quick analysis without complex setup (requires copy/paste):

python scripts/simple_pcap_analysis.py path/to/your/capture.pcap

This generates a markdown file you can copy and paste into Claude at claude.ai.

3. API Integration

For programmatic integration with Claude's API:

from claude_client import ClaudeClient  # Your implementation
from wireshark_mcp import WiresharkMCP
from wireshark_mcp.formatters import ClaudeFormatter

# Process the PCAP file
mcp = WiresharkMCP("capture.pcap")
context = mcp.generate_context()

# Format for Claude
formatter = ClaudeFormatter()
prompt = formatter.format_context(context, query="Analyze this network traffic")

# Send to Claude API
client = ClaudeClient(api_key="your_api_key")
response = client.analyze(prompt)

See the Claude Integration Guide for detailed API instructions.

Requirements

• Python 3.8+
• Wireshark/tshark installed and in your PATH
• fastmcp Python package

Contributing

Contributions are welcome! Areas where help is especially appreciated:

• Additional protocol analyzers
• Performance optimizations
• Documentation and examples
• Testing with diverse packet captures
• Web interface enhancements

See CONTRIBUTING.md for details on how to contribute.

License

This project is licensed under the MIT License - see the LICENSE file for details.