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spindl-workshop: MCP Response Spooling (CyberCon2026)

Hands-on companion repository for the CyberCon2026 workshop on MCP spooling architecture, built on spindl.

You will run the same simulated firewall MCP server twice, ask it the same security questions, and watch what happens to your client's context window.

  • Exercise 1 (naive mode): the server returns raw dumps. A 1,200 rule rulebase lands in your model's context in full.

  • Exercise 2 (spindl mode): the same server, same data, same tools, with spindl's response spooler enabled. Large results are stored server-side and you explore them with query, aggregate, and distinct tools.

All data is fabricated. The device, vendor, addresses, rules, and logs are fictional and generated deterministically, so everyone in the room sees identical data.

Prerequisites

  • uv installed (uv --version to confirm). uv will fetch a suitable Python (3.10+) automatically if needed.

  • An MCP client that supports local stdio servers. Tested with Claude Desktop and VS Code (Copilot agent mode). See clients/ for configuration snippets, including notes for ChatGPT/Codex users.

  • You should be comfortable editing your client's MCP configuration file.

Related MCP server: MCP-Firewall

Smoke test (do this before the workshop)

uvx --from git+https://github.com/Cognisn/spindl-workshop spindl-workshop --help

If you see the usage text with --mode {naive,spindl}, you are ready.

Exercise 1: the naive server

Configure your client with mode naive (snippets in clients/), then work through exercises/EXERCISE-1.md. You will ask questions such as:

  • Which enabled rules allow inbound RDP from the internet?

  • Which source IP generated the most denies in the last 24 hours?

Watch your client's context/token indicators while you do it.

Exercise 2: the spindl server

Change one word in your client config, naive to spindl, restart the client, and work through exercises/EXERCISE-2.md. Same questions. Note the spool summaries, then let the model drive fw_spooler_query, fw_spooler_aggregate, and fw_spooler_distinct.

What is in the box

Path

Purpose

data/firewall.json

Committed, deterministic fabricated data set

src/spindl_workshop/

The MCP server and its three firewall tools

exercises/

The two hands-on exercise sheets

clients/

Per-client MCP configuration snippets

tools/generate_data.py

Presenter-only data generator (seeded)

The tools exposed

With prefix fw, the server exposes:

  • fw_get_device_info: tiny response, use as a connectivity check

  • fw_get_rulebase: the full security policy (large)

  • fw_get_traffic_logs: 24 hours of traffic logs (very large)

  • fw_list_tools and fw_describe_tool: spindl's built-in skills guides

  • fw_spooler_list / fw_spooler_query / fw_spooler_aggregate / fw_spooler_distinct: present in spindl mode only

Licence

MIT. Fabricated data, no real systems were harmed.

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