Bagel lets you ask questions about robotics, drone, and IoT data (ROS 1/2 bags, MCAP, PX4/ArduPilot/Betaflight logs, CAN/MF4, live MQTT) in plain English. Every answer is computed by DuckDB SQL over the actual messages and the query is shown for audit. Bagel also has an intelligent edge data reduction pipeline: describe an event once, preview what would be kept, then run it on the robot. The plugin bundles the MCP connection (localhost:8000/sse; server runs in Docker, data never leaves the machine) plus four skills that teach the agent the server's own workflows: triage, pipeline authoring, live sinks, and export to Rerun / Lichtblick / PlotJuggler / LeRobot.
Install
- 1Add it in ChatGPT
Open Plugins in the ChatGPT sidebar (web or desktop), search for “Bagel” and select +. You'll be asked to sign in to any connected service on first use. Then type @ in a chat to call it.
Skills 4
- authoring-pipelines
Use when the user wants a bagel data pipeline — reducing a log to windows around events ("keep 30s around every hard brake"), recurring snippets/GIFs/exports, or any tasks-and-gates automation over robot data.
- exporting-visualizations
Use when the user wants to SEE robot data — visualize, plot, replay, or export a log or query result from bagel to a viewer or training format (Rerun, Lichtblick, PlotJuggler, LeRobot).
- operating-live-sinks
Use when subscribing to live robot data (MQTT, rosbridge) through bagel, managing standing pipelines that survive restarts, or when questions about live-buffer sizes and disk usage come up.
- triaging-robot-logs
Use when investigating a robot log or flight log with bagel — finding events, anomalies, or "what happened around X" in rosbags, MCAP, CAN, MDF4, ULog, or Betaflight files. Routes to the server's triage capability.
Things to ask
- “Summarize the metadata of ./data/sample/ros2/mcap”
- “Read the ERROR messages from ./data/sample/ros/log and summarize what went wrong”
- “Find every hard deceleration in my bag and keep 2 seconds around each”
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