WireMCP is a Model Context Protocol (MCP) server that enhances Large Language Models with network traffic analysis capabilities. It captures and processes live network data through Wireshark's tshark, enabling LLMs to assist with threat hunting, network diagnostics, and anomaly detection by providing structured context from network traffic.
tshark
installed and accessible in PATHClone the repository:
git clone https://github.com/0xkoda/WireMCP.git
cd WireMCP
Install dependencies:
npm install
Run the MCP server:
node index.js
Note: WireMCP will automatically detect tshark in your PATH or fall back to common install locations such as
/Applications/Wireshark.app/Contents/MacOS/tshark
on macOS.
Edit mcp.json
in Cursor's settings:
{
"mcpServers": {
"wiremcp": {
"command": "node",
"args": [
"/ABSOLUTE_PATH_TO/WireMCP/index.js"
]
}
}
}
The configuration file is typically located at /Users/YOUR_USER/Library/Application Support/Claude/claude_desktop_config.json
on macOS.
WireMCP works with any MCP-compliant client. Simply configure the client to use the command node /path/to/WireMCP/index.js
in their MCP server settings.
WireMCP provides several tools for network analysis:
capture_packets
: Captures live traffic and returns packet data as JSONget_summary_stats
: Provides protocol hierarchy statisticsget_conversations
: Shows TCP/UDP conversation statisticscheck_threats
: Captures IPs and checks them against the URLhaus blacklistcheck_ip_threats
: Performs targeted threat intelligence lookups for specific IP addressesanalyze_pcap
: Analyzes saved PCAP files to provide packet data in JSON formatextract_credentials
: Scans PCAP files for potential credentials from various protocolsWhen running the check_threats
tool, you might see output like:
Captured IPs:
174.67.0.227
52.196.136.253
Threat check against URLhaus blacklist:
No threats detected in URLhaus blacklist.
Using analyze_pcap
on a capture file produces structured JSON output:
{
"content": [{
"type": "text",
"text": "Analyzed PCAP: ./capture.pcap\n\nUnique IPs:\n192.168.0.2\n192.168.0.1\n\nProtocols:\neth:ethertype:ip:tcp\neth:ethertype:ip:tcp:telnet\n\nPacket Data:\n[{\"layers\":{\"frame.number\":[\"1\"],\"ip.src\":[\"192.168.0.2\"],\"ip.dst\":[\"192.168.0.1\"],\"tcp.srcport\":[\"1550\"],\"tcp.dstport\":[\"23\"]}}]"
}]
}
LLMs can interpret these outputs to provide:
There are two ways to add an MCP server to Cursor. The most common way is to add the server globally in the ~/.cursor/mcp.json
file so that it is available in all of your projects.
If you only need the server in a single project, you can add it to the project instead by creating or adding it to the .cursor/mcp.json
file.
To add a global MCP server go to Cursor Settings > MCP and click "Add new global MCP server".
When you click that button the ~/.cursor/mcp.json
file will be opened and you can add your server like this:
{
"mcpServers": {
"cursor-rules-mcp": {
"command": "npx",
"args": [
"-y",
"cursor-rules-mcp"
]
}
}
}
To add an MCP server to a project you can create a new .cursor/mcp.json
file or add it to the existing one. This will look exactly the same as the global MCP server example above.
Once the server is installed, you might need to head back to Settings > MCP and click the refresh button.
The Cursor agent will then be able to see the available tools the added MCP server has available and will call them when it needs to.
You can also explictly ask the agent to use the tool by mentioning the tool name and describing what the function does.