Building an MCP Server for PCAP Analysis — Looking for Architecture & Best Practice Suggestions #762
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Khushboo1910
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A good headstart would be to analyze this project https://github.com/weirdmachine64/SharkMCP , it's a great reference . |
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Hello Experts,
I’m planning to build an MCP (Model Context Protocol) server focused on PCAP/network traffic analysis and would love input from the community. I have gone through this article but I still felt there might be an improvement areas. Link- https://skywork.ai/skypage/en/wireshark-mcp-server-guide-ai-engineers/1980151768098840576
The goal is to create an MCP server that allows an LLM to intelligently analyze .pcap files, inspect protocols, detect anomalies, and assist with troubleshooting/security investigations.
I’m currently designing the architecture and trying to identify:
What are the ideal tools/functions an MCP server for PCAP analysis should expose?
Some ideas:
analyze_pcap() → protocol summary, conversations, statistics
detect_anomalies() → suspicious traffic patterns
live_capture() → real-time interface capture
Resources
What resources should ideally be exposed to the LLM?
Special Prompts
What instructions are important for safe and accurate analysis?
Best Practices
Looking for recommendations around:
a. MCP architecture patterns
b. Tool granularity (small tools vs large tools)
c. Performance optimization for large PCAPs
d. Streaming analysis workflows
e. Security considerations
f. Multi-agent approaches for protocol analysis
g. Best way to expose tshark functionality safely
h. Handling token/context limitations with large captures
If anyone has built something similar — especially around Wireshark, tshark, MCP-based security tooling — I’d really appreciate your insights, architecture ideas, or open-source references.
Note: Further, I can use this MCP tool to analyze logs from various network security tools such as Sysinternals, NetMon, ProcMon, etc. Please also add your comments on whether this can be achieved using a single MCP server.
Thanks!
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