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agentic-debugger

by iarmankhan
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agentic-debugger

An MCP (Model Context Protocol) server that enables interactive debugging with code instrumentation for AI coding assistants. Inspired by Cursor's debug mode.

Works with any MCP-compatible AI coding tool:

  • Claude Code

  • Cursor

  • Windsurf

  • Cline

  • GitHub Copilot

  • Kiro

  • Zed

  • And more...

Features

  • Live code instrumentation - Inject debug logging at specific lines

  • Variable capture - Log variable values at runtime

  • Multi-language support - JavaScript, TypeScript, and Python

  • Browser support - CORS-enabled for browser JS debugging

  • Clean removal - Region markers ensure instruments are fully removed

Installation

Using npx (recommended)

Add to your MCP configuration:

{ "mcpServers": { "debug": { "command": "npx", "args": ["-y", "agentic-debugger"] } } }

Configuration file locations:

  • Claude Code: ~/.mcp.json

  • Cursor: .cursor/mcp.json in your project or ~/.cursor/mcp.json

  • Other tools: Check your tool's MCP documentation

Global install

npm install -g agentic-debugger

Then configure:

{ "mcpServers": { "debug": { "command": "agentic-debugger" } } }

Available Tools

Tool

Description

start_debug_session

Start HTTP server for log collection

stop_debug_session

Stop server and cleanup

add_instrument

Insert logging code at file:line

remove_instruments

Remove debug code from file(s)

list_instruments

Show all active instruments

read_debug_logs

Read captured log data

clear_debug_logs

Clear the log file

How It Works

  1. Start session - Spawns a local HTTP server (default port 9876)

  2. Add instruments - Injects fetch() calls that POST to the server

  3. Reproduce bug - Run your code, instruments capture variable values

  4. Analyze logs - Read the captured data to identify issues

  5. Cleanup - Remove all instruments and stop the server

Debug Workflow Example

You: "Help me debug why the total is NaN" AI Assistant: 1. Starts debug session 2. Reads your code to understand the logic 3. Adds instruments at suspicious locations 4. "Please run your code to reproduce the issue" You: *runs code* "Done" AI Assistant: 5. Reads debug logs 6. "I see `discount` is undefined at line 15..." 7. Removes instruments 8. Fixes the bug 9. Stops debug session

Instrument Examples

JavaScript/TypeScript

// #region agentic-debug-abc123 fetch('http://localhost:9876/log', { method: 'POST', headers: { 'Content-Type': 'application/json' }, body: JSON.stringify({ id: 'abc123', location: 'cart.js:15', timestamp: Date.now(), data: { total, discount, items } }) }).catch(() => {}); // #endregion agentic-debug-abc123

Python

# region agentic-debug-abc123 try: import urllib.request as __req, json as __json __req.urlopen(__req.Request( 'http://localhost:9876/log', data=__json.dumps({ 'id': 'abc123', 'location': 'cart.py:15', 'timestamp': __import__('time').time(), 'data': {'total': total, 'discount': discount} }).encode(), headers={'Content-Type': 'application/json'} )) except: pass # endregion agentic-debug-abc123

Supported Languages

Language

Extensions

JavaScript

.js, .mjs, .cjs

TypeScript

.ts, .tsx

Python

.py

Requirements

  • Node.js >= 18.0.0

  • An MCP-compatible AI coding assistant

License

MIT

Install Server
A
security – no known vulnerabilities
A
license - permissive license
A
quality - confirmed to work

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