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Debugium

by Algirasversion 1.0.0i★ –iRuns on your computer
Registry nameio.github.Algiras/debugium

Install

Overview

Description from the maker (original English)

AI-driven live debugger with MCP bridge for Python, JS, TS, Rust, Java, C/C++

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "debugium": {
      "command": "npx",
      "args": [
        "-y",
        "@algiras/debugium"
      ]
    }
  }
}

Run this in your terminal

claude mcp add debugium -- npx -y @algiras/debugium

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "debugium": {
      "command": "npx",
      "args": [
        "-y",
        "@algiras/debugium"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "debugium": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@algiras/debugium"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account Algiras, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32410 servers in this category
  • Published to the registry more recently than 3% of the other 32410 servers in this category
  • Basic checks equal to or better than 100% of the other 32410 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Debugium safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.0) reached the registry 8 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, debuff

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Spec Driven Development

by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated yesterday
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debuff

by debuffjp

Let coding agents play, test and tune your 2D web game: live state, explained errors, replays, fuzz.

Runs on your computerUpdated today
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Debugium

A multi-language debugger with a real-time web UI and LLM integration via MCP.

Debug Python, JavaScript, TypeScript, C, C++, Rust, Java, Scala, and WebAssembly programs from your browser — with AI-driven analysis through the Model Context Protocol.


Features

Web UI
  • Real-time web UI — source viewer, breakpoints, variables (recursive expansion), call stack, console, timeline, watch expressions, findings — all updated live via WebSocket
  • Multi-tab source viewer — open multiple files, click stack frames to navigate
  • Variable search — filter variables by name with recursive expansion
  • Changed-variable highlighting — variables that changed since last stop shown in orange
  • Thread selector — switch between threads in multi-threaded programs
  • Panel collapse & resize — drag to resize, toggle to collapse; Slim / Standard / Full layout presets
  • Dark / light mode toggle
  • Auto-reconnect — UI reconnects after a dropped WebSocket, with visual status indicator
  • Keyboard shortcuts — F5 continue, F10 step over, F11 step in, Shift+F11 step out, Ctrl/Cmd+D dark mode
  • Button animations — in-flight spinner and completion flash for debug commands
Debugging
  • Multi-language — Python (debugpy), Node.js/TypeScript (js-debug), C/C++/Rust (lldb-dap), Java (java-debug), Scala (Metals), WebAssembly (lldb-dap), or any DAP adapter via dap.json
  • Comprehensive DAP coverage — 35+ DAP requests: breakpoints, stepping, goto, memory read/write, disassembly, and more
  • Breakpoints — conditional, logpoints, hit-count, function, data (watchpoints), exception, run-to-cursor (continue_until)
  • Multi-session — debug multiple programs simultaneously, with child session routing (js-debug)
  • Remote debugging — attach to debugpy, JDWP, or Node inspector running on another machine or container
LLM / MCP Integration
  • 64 MCP tools — the full debug session exposed to Claude or any LLM
  • Capability-gated tools — tools automatically shown/hidden based on adapter capabilities
  • Compound tools — get_debug_context (orient in one call), step_until, step_until_change, run_until_exception, explain_exception, get_call_tree, compare_snapshots, find_first_change
  • Execution timeline — every stop recorded with changed variables and stack summary
  • Watch expressions — evaluated automatically at every breakpoint, manageable by LLM or UI
  • Annotations & findings — pin notes to source lines, record conclusions visible in the UI
  • Session export/import — save and restore debugging knowledge across sessions
CLI Control
  • Full CLI — 13 subcommands to drive sessions from a second terminal without the web UI
  • Auto-discovery — port file at ~/.debugium/port, session logs in ~/.debugium/sessions/

Install

Claude Code Plugin (recommended)
/plugin marketplace add Algiras/debugium

/plugin install debugium@debugium

Then add to your project's .mcp.json (see MCP Tools below).

macOS / Linux binary
curl -fsSL https://raw.githubusercontent.com/Algiras/debugium/main/install.sh | bash
From source
# Prerequisites: Rust stable + wasm-pack

cargo install wasm-pack

Build UI

wasm-pack build crates/debugium-ui --target web --out-dir pkg cp crates/debugium-ui/pkg/cm_init.js crates/debugium-ui/dist/pkg/ cp crates/debugium-ui/pkg/debugium_ui.js crates/debugium-ui/dist/pkg/ cp crates/debugium-ui/pkg/debugium_ui_bg.wasm crates/debugium-ui/dist/pkg/

Build & install server

cargo install --path crates/debugium-server


Usage

Debug a Python file
debugium launch my_script.py --adapter python
Debug a Node.js / TypeScript file
debugium launch app.js --adapter node

debugium launch app.ts --adapter typescript

Debug C / C++ / Rust
# C or C++ (compile with -g for debug info)

cc -g -O0 main.c -o main && debugium launch ./main --adapter lldb c++ -g -O0 main.cpp -o main && debugium launch ./main --adapter lldb

Rust

cargo build && debugium launch target/debug/my_binary --adapter lldb

Debug Java / Scala
# Java (requires microsoft/java-debug adapter)

debugium launch MainClass --adapter java

Scala (connect to a running Metals DAP server)

debugium launch build-target --adapter metals debugium launch build-target --adapter metals:5005 # custom port

Attach to a running process (remote debugging)
# Python (debugpy listening on port 5678)

debugium attach --port 5678 --adapter python

Java (JDWP on port 5005)

debugium attach --port 5005 --adapter java

Node.js (inspector on port 9229)

debugium attach --port 9229 --adapter node

Or via MCP: attach_session(port=5678, adapter="python", breakpoints=["/path/app.py:42"])

Use a custom adapter via dap.json
# Create a dap.json (see dap.json.example) then:

debugium launch my_program --config ./dap.json

Or place dap.json in cwd / .debugium/ for auto-discovery:

debugium launch my_program # finds ./dap.json automatically

Set initial breakpoints
debugium launch my_script.py --adapter python \

--breakpoint /abs/path/my_script.py:42 \ --breakpoint /abs/path/helpers.py:15

Enable LLM / MCP integration

Add a .mcp.json to your project root (Claude Code picks this up automatically):

{

"mcpServers": { "debugium": { "command": "debugium", "args": ["mcp"] } } }

Then launch the session normally — the MCP server connects to whichever port is active:

debugium launch my_script.py --adapter python --breakpoint /abs/path/my_script.py:42

Claude Code will now have access to all Debugium MCP tools. See CLAUDE.md for the recommended workflow and SKILL.md for the full tool reference.


CLI Control Commands

Once a session is running (debugium launch …), you can drive it from a second terminal — or from an LLM agent — without touching the web UI.

Port is auto-discovered from ~/.debugium/port; override with --port.

Global flags (all subcommands)
FlagDefaultDescription
--port PORT~/.debugium/portServer port to connect to
--session IDdefaultSession to target
--jsonoffPrint raw JSON instead of human-readable output
Inspection
debugium sessions                  # list active sessions

debugium threads # list threads debugium stack # show call stack debugium vars # show local variables (auto-resolves top frame) debugium vars --frame-id 2 # show variables for a specific frame debugium eval "len(fibs)" # evaluate expression in top frame debugium eval "x + 1" --frame-id 2 debugium source path/to/file.py # print full source file debugium source path/to/file.py --line 43 # windowed ±10 lines with → marker debugium context # full snapshot: paused-at, stack, locals, source, breakpoints debugium context --compact # same but truncated (3 frames, 10 vars)

Breakpoints
debugium bp set FILE:LINE [FILE:LINE …]   # set breakpoints (replaces existing in that file)

debugium bp list # list all breakpoints debugium bp clear # clear all breakpoints

Execution control
debugium continue                  # resume execution

debugium step over # step over (next line) debugium step in # step into a function call debugium step out # step out of current function

UI annotations (visible in the web UI)
debugium annotate FILE:LINE "message" [--color info|warning|error]

debugium finding "message" [--level info|warning|error]

Example workflow
# Terminal A — start the session

debugium launch tests/target_python.py --adapter python \ --breakpoint "$(pwd)/tests/target_python.py:43"

Terminal B (or LLM agent) — inspect and drive it

debugium sessions debugium stack debugium vars debugium eval "len(fibs)" debugium bp set tests/target_python.py:49 debugium continue # runs to line 49 debugium vars debugium step over debugium context --json # machine-readable snapshot debugium annotate tests/target_python.py:43 "called here" --color info debugium finding "fibs has 10 elements" --level info debugium bp clear


MCP Tools

When connected via MCP, 64 tools are available. Key ones:

CategoryTools
Orientget_debug_context ★ (paused location + locals + stack + source in one call)
Breakpointsset_breakpoint, set_breakpoints, set_logpoint, list_breakpoints, clear_breakpoints, set_function_breakpoints, set_exception_breakpoints, set_data_breakpoint, list_data_breakpoints, clear_data_breakpoints, breakpoint_locations
Executioncontinue_execution, step_over, step_in, step_out, pause, goto, disconnect, terminate, restart
Inspectionget_stack_trace, get_scopes, get_variables, evaluate, get_threads, get_source, get_capabilities, loaded_sources, source_by_reference, step_in_targets
Mutationset_variable, set_expression
Outputget_console_output, wait_for_output (with from_line to avoid stale matches)
Memoryread_memory, write_memory, disassemble (native debugging)
Historyget_timeline, get_variable_history, compare_snapshots, find_first_change
Annotationsannotate, get_annotations, add_finding, get_findings
Watchesadd_watch, remove_watch, get_watches
Compoundstep_until, step_until_change, continue_until, run_until_exception, explain_exception, get_call_tree, restart_frame
Sessionget_sessions, list_sessions, launch_session, attach_session, stop_session, export_session, import_session
Controlgoto_targets, cancel_request

Note: step_over, step_in, and step_out are blocking — they wait for the

adapter to pause before returning. Safe to chain back-to-back without sleeps.

continue_execution returns console_line_count for use with wait_for_output.

Tools like read_memory, goto, and restart_frame only appear when the adapter supports them.

See SKILL.md for the full reference with input schemas.


Keyboard Shortcuts

KeyAction
F5Continue
F10Step Over
F11Step Into
Shift+F11Step Out
Ctrl/⌘+DToggle dark/light mode

Architecture

debugium-server (Rust + Axum)

├── DAP proxy — spawns / attaches to debug adapters (debugpy, js-debug, lldb-dap, java-debug, Metals, custom) ├── HTTP API — /state, /sessions, /annotations, /findings, /watches, /timeline ├── WebSocket — broadcasts DAP events + enriched stop data (changed vars, timeline) to UI ├── MCP stdio — JSON-RPC 2.0 server exposing 64 tools for LLM integration ├── CLI control — 13 subcommands to drive sessions from a second terminal └── ~/.debugium/ — port file, session logs (events.ndjson), debug log

debugium-ui (Leptos + WASM) ├── CodeMirror 6 — source viewer with breakpoint gutters, exec arrow, LLM annotations, multi-tab ├── Reactive panels — Variables, Stack, Breakpoints, Finding

Only the beginning is shown; read the rest in the repo

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