I built and open-sourced PacketVoyageβan Agent Skill & MCP server that turns boring traceroute
outputs into fascinating stories about physics, geography, and undersea cables.
Model Context Protocol (MCP) Server & Agent Skill for educational network traceroute analysis, fiber-optic physics verification, and packet voyage storytelling.Zero external commercial APIs, zero bundled copyright data β pure physical laws and detective insight.
PacketVoyage is built around two complementary layers designed specifically for AI-native workflows:
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β AI Agent (LLM) β
ββββββββββββββββ¬βββββββββββββββββββββββββββ¬βββββββββββββββ
β β
βΌ βΌ
ββββββββββββββββββββββββββββββββ ββββββββββββββββββββββββββββββββ
β π§ Agent Skill β β π οΈ MCP Server β
β (Knowledge / Playbook) β β (Capabilities / Execution)β
ββββββββββββββββββββββββββββββββ€ ββββββββββββββββββββββββββββββββ€
β β’ Speed of Light in Fiber β β β’ analyze_voyage_text β
β (~0.67c, ~10ms / 1,000km) β β β’ voyage_investigate β
β β’ Control vs Data Plane math β β β’ run_protocol_experiment β
β β’ Disproving GeoIP illusions β β β’ research_host β
β β’ Decision Flow & Heuristics β β β’ list_known_iata_airports β
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Ever wondered whatβs actually happening behind a trace like this?
1 gateway (192.168.1.1) 0.8 ms
2 * * *
3 ae-1.tokyo-hnd.bb.net (203.0.113.1) 2.1 ms
4 xe-0-0.sjc-core.bb.net (198.51.100.25) 88.5 ms
5 one.one.one.one (1.1.1.1) 88.7 ms
Behind these lines lies real-world physics:
β’ The * * * at Hop 2 isn't packet loss: Normal traffic runs at line rate in hardware ASICs (Data Plane), while diagnostic ICMP responses are rate limited by router CPUs (Control Plane).
β’ The +86ms jump: Light travels in silica glass fiber at ~200,000 km/s (~10 ms RTT per 1,000 km). Tokyo to Silicon Valley is ~8,300 km, so ~83 ms is the theoretical speed-of-light limit across the Pacific ocean floor.
β’ Hidden IATA codes: Hostnames like tokyo-hnd (Haneda) and sjc-core (San Jose) reveal the subsea cable route (e.g., JUNO / PC-1).
For students and general engineers, understanding what happens inside traceroute can be difficult. Letβs have AI explain it instead.
### π’ Example AI Output
Feed that trace to Claude or any MCP-enabled AI agent by packetvoyage skill
β π Route: Tokyo (HND) π [JUNO Submarine Cable] β San Jose (SJC) (~8,335 km)
β π Physics Check: Latency spiked from 2.1 ms β 88.5 ms (+86.4 ms), perfectly matching the speed of light in transpacific optical fiber. Hop 2
β asterisks are standard CPU control-plane rate limiting.
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Add it to Claude Code with one command:
claude mcp add packetvoyage -- uvx --from git+https://github.com/europeanplaice/packetvoyage.git packetvoyage
For Claude Desktop / Cursor / Antigravity, add this to your MCP config:
{
"mcpServers": {
"packetvoyage": {
"command": "uvx",
"args": ["--from", "git+https://github.com/europeanplaice/packetvoyage.git", "packetvoyage"]
}
}
}
Check out the repo and give your next traceroute a physical voyage!
π GitHub: europeanplaice/packetvoyage https://github.com/europeanplaice/packetvoyage