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WireMCP

An MCP for WireShark (tshark). Empower LLM's with realtime network traffic analysis capability

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创建于 2025-03-28 · 更新于 2026-10-16 · 今日第 6644 名
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关键参数与规格
关键参数与规格
参数值
语言JavaScript
类别AI Engineering
子类别Give agent tools
关键词Agent-ready APIs, MCP, Security, Unstructured data extraction
星标数596
分叉数65
贡献者1
创建日期2025-03-28
更新日期2026-10-16
1 天星标数1
7 天星标数5
排名6,644
上次排名16,172
排名变化9,528
7 天星标排名5,767
上次 7 天星标排名5,306
7 天星标排名变化-461
总星标排名16,868
上次总星标排名16,871
总星标排名变化3
README 摘录

WireMCP WireMCP is a Model Context Protocol (MCP) server designed to empower Large Language Models (LLMs) with real-time network traffic analysis capabilities. By leveraging tools built on top of Wireshark's , WireMCP captures and processes live network data, providing LLMs with structured context to assist in tasks like threat hunting, network diagnostics, and anomaly detection. Features WireMCP exposes the following tools to MCP clients, enhancing LLM understanding of network activity: ** **: Captures live traffic and returns raw packet data as JSON

, enabling LLMs to analyze packet-level details (e. ** **: Provides protocol hierarchy statistics, giving LLMs an overview of traffic composition (e. ** **: Delivers TCP/UDP conversation statistics, allowing LLMs to track communication flows between endpoints. ** **: Captures IPs and checks them against the URLhaus blacklist, equipping LLMs with threat intelligence context for identifying malicious activity. ** **: Performs targeted threat intelligence lookups for specific IP addresses against multiple threat feeds, providing detailed reputation and threat data. ** **: Analyzes PCAP files to provide comprehensive packet data in

JSON format, enabling detailed post-capture analysis of network traffic. ** **: Scans PCAP files for potential credentials from various protocols (HTTP Basic Auth, FTP, Telnet), aiding in security audits and forensic analysis. How It Helps LLMs WireMCP bridges the gap between raw network data and LLM comprehension by: **Contextualizing Traffic**: Converts live packet captures into structured outputs (JSON, stats) that LLMs can parse and reason about. **Threat Detection**: Integrates IOCs (currently URLhaus) to flag suspicious IPs, enhancing LLM-driven security analysis

. **Diagnostics**: Offers detailed traffic insights, enabling LLMs to assist with troubleshooting or identifying anomalies. **Narrative Generation**: LLM's can Transform complex packet captures into coherent stories, making network analysis accessible to non-technical users. Installation Prerequisites Mac / Windows / Linux Wireshark (with installed and accessible in PATH) Node. js (v16+ recommended) npm (for dependency installation) Setup 1. Run the MCP server: **Note**: Ensure is in your PATH. WireMCP will auto-detect it or fall back to common install locations (e. Usage with

MCP Clients WireMCP works with any MCP-compliant client. Below are examples for popular clients: Example 1: Cursor Edit in Cursor -> Settings -> MCP : **Location (macOS)**: Other Clients This MCP will work well with any client. Use the command in their MCP server settings. Example Output Running might yield: Running on a capture file: LLMs can use these outputs to: Provide natural language explanations of network activity Identify patterns and potential security concerns Offer context-aware recommendations Generate human-readable reports

Roadmap **Expand IOC Providers**: Currently uses URLhaus for threat checks. Future updates will integrate additional sources (e. , IPsum, Emerging Threats) for broader coverage. Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change. License MIT Acknowledgments Wireshark/tshark team for their excellent packet analysis tools Model Context Protocol community for the framework and specifications URLhaus for providing threat intelligence data

常见问题

记录了多少星标和分叉?

0xKoda/WireMCP 有 596 个星标和 65 个分叉。

仓库排名是多少?

0xKoda/WireMCP 排名第 6,644。

记录的语言和类别是什么?

0xKoda/WireMCP 有 596 个星标,语言为 JavaScript,类别为 AI Engineering。

哪个仓库排名最接近?

0xKoda/WireMCP 与 nicobailon/pi-interactive-shell 比较,后者排名第 6,646,有 595 个星标。

README

WireMCP

WireMCP is a Model Context Protocol (MCP) server designed to empower Large Language Models (LLMs) with real-time network traffic analysis capabilities. By leveraging tools built on top of Wireshark's tshark, WireMCP captures and processes live network data, providing LLMs with structured context to assist in tasks like threat hunting, network diagnostics, and anomaly detection.

Features

WireMCP exposes the following tools to MCP clients, enhancing LLM understanding of network activity:

  • capture_packets: Captures live traffic and returns raw packet data as JSON, enabling LLMs to analyze packet-level details (e.g., IP addresses, ports, HTTP methods).
  • get_summary_stats: Provides protocol hierarchy statistics, giving LLMs an overview of traffic composition (e.g., TCP vs. UDP usage).
  • get_conversations: Delivers TCP/UDP conversation statistics, allowing LLMs to track communication flows between endpoints.
  • check_threats: Captures IPs and checks them against the URLhaus blacklist, equipping LLMs with threat intelligence context for identifying malicious activity.
  • check_ip_threats: Performs targeted threat intelligence lookups for specific IP addresses against multiple threat feeds, providing detailed reputation and threat data.
  • analyze_pcap: Analyzes PCAP files to provide comprehensive packet data in JSON format, enabling detailed post-capture analysis of network traffic.
  • extract_credentials: Scans PCAP files for potential credentials from various protocols (HTTP Basic Auth, FTP, Telnet), aiding in security audits and forensic analysis.

How It Helps LLMs

WireMCP bridges the gap between raw network data and LLM comprehension by:

  • Contextualizing Traffic: Converts live packet captures into structured outputs (JSON, stats) that LLMs can parse and reason about.
  • Threat Detection: Integrates IOCs (currently URLhaus) to flag suspicious IPs, enhancing LLM-driven security analysis.
  • Diagnostics: Offers detailed traffic insights, enabling LLMs to assist with troubleshooting or identifying anomalies.
  • Narrative Generation: LLM's can Transform complex packet captures into coherent stories, making network analysis accessible to non-technical users.

Installation

Prerequisites

  • Mac / Windows / Linux
  • Wireshark (with tshark installed and accessible in PATH)
  • Node.js (v16+ recommended)
  • npm (for dependency installation)

Setup

  1. Clone the repository:

    git clone https://github.com/0xkoda/WireMCP.git
    cd WireMCP
    
  2. Install dependencies:

    npm install
    
  3. Run the MCP server:

    node index.js
    

Note: Ensure tshark is in your PATH. WireMCP will auto-detect it or fall back to common install locations (e.g., /Applications/Wireshark.app/Contents/MacOS/tshark on macOS).

Usage with MCP Clients

WireMCP works with any MCP-compliant client. Below are examples for popular clients:

Example 1: Cursor

Edit mcp.json in Cursor -> Settings -> MCP :

{
  "mcpServers": {
    "wiremcp": {
      "command": "node",
      "args": [
        "/ABSOLUTE_PATH_TO/WireMCP/index.js"
      ]
    }
  }
}

Location (macOS): /Users/YOUR_USER/Library/Application Support/Claude/claude_desktop_config.json

Other Clients

This MCP will work well with any client. Use the command node /path/to/WireMCP/index.js in their MCP server settings.

Example Output

Running check_threats might yield:

Captured IPs:
174.67.0.227
52.196.136.253

Threat check against URLhaus blacklist:
No threats detected in URLhaus blacklist.

Running analyze_pcap on a capture file:

{
  "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 use these outputs to:

  • Provide natural language explanations of network activity
  • Identify patterns and potential security concerns
  • Offer context-aware recommendations
  • Generate human-readable reports

Roadmap

  • Expand IOC Providers: Currently uses URLhaus for threat checks. Future updates will integrate additional sources (e.g., IPsum, Emerging Threats) for broader coverage.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

License

MIT

Acknowledgments

  • Wireshark/tshark team for their excellent packet analysis tools
  • Model Context Protocol community for the framework and specifications
  • URLhaus for providing threat intelligence data
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