MCU-AI-Debug: Advanced MCU Debugging with AI & Real-time Visualization

High-performance MCU debugger extension with AI/MCP integration, hardware-accelerated real-time graphing, and local data recording, forked from the mcu-debug project.

1. Model Context Protocol (MCP) Server

Embedded MCP server that exposes debugger state to external AI agents (Copilot, Cursor, Claude Desktop, etc.) without complex scripting.

Quick Start

1. Run MCU-AI-Debug: Generate MCP Configuration for AI Agents from the Command Palette.
2. Choose a configuration format and send the generated prompt mcu-debug-mcp.md to your AI agent for fetching variables.

Key AI Tools

• get_livewatch_variables: Snapshot of current debug state.
• add_livewatch_variable: Add expressions via AI.
• record_livewatch_variables: AI-driven data capture for a fixed duration.
• record_livewatch_variables_manual: AI-driven data capture with user-controlled Start/Stop buttons.

2. Editor Integration & Local Recording

Make debugging workflows faster by adding expressions directly from the editor and recording Live Watch data to local files.

Quick Add from Editor

Select a C/C++ expression in the editor, right-click and choose "Add to Live Watch" to push the expression into the Live Watch panel instantly.

Local Recording (CSV / JSONL)

Record selected variables to a local file (CSV or JSONL) with high-precision timestamps. Supports automatic sanitization of GDB value formats.

3. High-Performance Real-time Grapher

Hardware-accelerated HTML5 Canvas rendering engine for real-time variable visualization.

• Dual Display Modes: Switch between "Split Mode" (independent Y-axes) and "Overlay Mode" (shared Y-axis).
• Oscilloscope Auto-scroll: Real-time scrolling with manual "PAN MODE" for history navigation.
• Precision Zoom: Dedicated sliders and mouse wheel support for Time and Y axes.

4. Relationship with Upstream

MCU-AI-Debug is a stable, production-ready fork of the mcu-debug project.

• Lean & Stable: Only mature, verified features are included to ensure a reliable engineering workflow.
• AI-First: Deep integration with Model Context Protocol (MCP) for modern AI-assisted debugging.
• Enhanced UI: Built-in high-performance visualization tools not found in the upstream.

5. Licenses

This project uses a multi-component license model:

• VS Code Extension: MIT License
• Rust Helper Binaries: Apache License 2.0

Note: This is an unofficial fork and is not affiliated with or endorsed by the upstream maintainers.