# Wireshark MCP Server

> Use this tool when you need to automate network packet analysis and protocol inspection for traffic forensics, allowing AI clients to analyze PCAP files securely and ephemerally. It solves problems related to network security, performance, and troubleshooting by providing a stateless server for synchronized packet capture file analysis. Inputs include PCAP files from GitHub, with outputs featuring detailed packet analysis and inspection results.

Canonical page: https://skillsregistry.net/skills/presidio-federal-wireshark-mcp-container  
JSON: https://api.skillsregistry.net/v1/skills/presidio-federal-wireshark-mcp-container

## Description

A containerized server that enables AI clients to perform automated network packet analysis, protocol inspection, and traffic forensics using Wireshark/tshark. It features a stateless design that synchronizes PCAP files directly from GitHub for secure and ephemeral analysis sessions.

## Trust

- **Trust score (0–1):** 0.91
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** version-control
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/jhywyd8bxy)
- **Repository:** <https://github.com/Presidio-Federal/wireshark-mcp-container>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "presidio-federal-wireshark-mcp-container"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/presidio-federal-wireshark-mcp-container` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/presidio-federal-wireshark-mcp-container/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt