AI Debugger
Bringing the debugging we know and love as human programmers to our AI agents – debug any supported language with breakpoints, variable/state inspection, and stepping, to supercharge agents' capabilities to reason about runtime code.
README
AI Debugger
<!-- mcp-name: io.github.ai-debugger-inc/aidb -->
AI-Powered Debugging for Every Language
AI Debugger (AIDB) brings the proven Debug Adapter Protocol (DAP) ecosystem to AI agents through a standardized Model Context Protocol (MCP) interface. Debug Python, JavaScript, TypeScript, and Java programs using the same battle-tested adapters that power VS Code—no IDE required, no heavyweight dependencies, just powerful debugging at your AI assistant's fingertips.
Read the Docs | Join Discord | Star on GitHub
Quick Install
Get started with Python debugging in under 60 seconds:
pip install ai-debugger-inc
Add to your MCP client settings (Claude Code, Cline, Cursor, etc.):
{
"mcpServers": {
"ai-debugger": {
"command": "python",
"args": ["-m", "aidb_mcp"]
}
}
}
Ask your AI assistant:
"Initialize debugging for Python. Debug
app.pywith a breakpoint at line 25."
JavaScript/Java? Visit the docs for multi-language setup.
Why AI Debugger?
Standalone & Zero Heavy Dependencies
No VS Code required. No heavyweight IDEs. Just install with pip and you're debugging––works on macOS, Linux, and Windows (WSL supported).
The core Python dependencies are lightweight and minimal:
dependencies = [
"aiofiles",
"mcp",
"psutil"
]
Debug adapters are built during the release pipeline and are published as
release artifacts. Once the ai-debugger-inc package is installed, your agent
will use the download tool to fetch the appropriate adapter binaries
automatically on first run.
Multi-Language from Day One
Debug Python, JavaScript, TypeScript, and Java with a single MCP server. AIDB is designed to support all DAP-compatible adapters, with more languages coming.
Built on the DAP Standard
AIDB uses the same Debug Adapter Protocol that powers VS Code debugging. We integrate with proven, open-source debug adapters:
- Python: debugpy (Microsoft)
- JavaScript/TypeScript: vscode-js-debug (Microsoft)
- Java: java-debug (Microsoft)
This means you get reliable, well-maintained debugging that "just works" with established patterns developers already trust.
VS Code Integration (Without VS Code)
Already have complex debug configurations in launch.json? AIDB can use them
directly—making sophisticated debugging setups portable and shareable across
teams without requiring VS Code installations.
Advanced Debugging Features
- Framework detection: Auto-detects pytest, jest, django, spring, flask, and more
- Conditional breakpoints: Break on
user.role == "admin"or after N hits - Logpoints: Log values without pausing execution
- Live code patching: Modify functions at runtime during debugging
Future-Ready Architecture
AIDB is built for where AI-assisted development is heading:
- CI/CD Debugging: Imagine test failures in your pipeline automatically triggering debug sessions for deeper RCA
- Agent Tooling: Native debugging capabilities for autonomous AI agents
- Cross-Platform Consistency: Same debugging API across all environments
How It Works
┌──────────────────────────────────────────────────────────────────┐
│ Your AI Assistant │
│ (Claude, GPT, Local LLMs) │
└────────────────────────────────┬─────────────────────────────────┘
│
▼
MCP Protocol
┌──────────────────────────────────────────────────────────────────┐
│ AI Debugger MCP Server │
│ Agent-Optimized Tools (init, step, inspect, etc.) │
└────────────────────────────────┬─────────────────────────────────┘
│
▼
AIDB Core API
┌──────────────────────────────────────────────────────────────────┐
│ Debug Adapter Protocol │
│ Language-Agnostic Debugging Interface │
└───────────┬────────────────────┼────────────────────┬────────────┘
│ │ │
▼ ▼ ▼
┌───────────────┐ ┌─────────────────┐ ┌───────────────┐
│ debugpy │ │ vscode-js-debug │ │ java-debug │
│ (Python) │ │ (JS/TS) │ │ (Java) │
└───────┬───────┘ └────────┬────────┘ └───────┬───────┘
│ │ │
▼ ▼ ▼
Your Python Your Node.js Your Java
Program Program Program
The Bridge Between AI and Proven Tools
AI Debugger acts as a translation layer, exposing the mature Debug Adapter Protocol ecosystem to AI agents through a clean, agent-optimized MCP interface. Your AI assistant gets powerful debugging capabilities, and you get the reliability of debug adapters used by millions of developers worldwide.
Learn more about the architecture →
Supported Languages
| Language | Python | JavaScript/TypeScript | Java |
|---|---|---|---|
| Status | ✔ Available | ✔ Available | ✔ Available |
| Versions | 3.10+ | Node 18+ | JDK 17+ |
| Platforms | All | All | All |
| Debug Adapter | debugpy | vscode-js-debug | java-debug |
Platforms: macOS, Linux, Windows (WSL recommended; native support in progress)
Coming Soon: Built to support all DAP-compatible adapters––AIDB is designed to become the debugging standard for AI systems across every popular language and framework.
Documentation
Getting Started
- Quickstart
Guide
- Install and debug in 5 minutes
- Core
Concepts
- Sessions, breakpoints, execution flow
- Language
Guides
- Python, JavaScript, Java examples
Technical Reference
- MCP Tools
Reference
- Complete tool documentation
- API
Documentation
- Python API reference
- Advanced
Workflows
- Remote debugging, multi-session
Architecture & Design
- How It
Works
- System architecture deep dive
- DAP Protocol
Guide
- Debug Adapter Protocol reference
Development Setup
Prerequisites: Python 3.10+, Docker
Initial setup:
bash scripts/install/src/install.sh -v
./dev-cli info
./dev-cli completion install --yes # optional
Common commands:
./dev-cli test run --coverage
./dev-cli docs serve --build-first -p 8000
Project Structure
aidb/: Core debugging API, language adapters, session managementaidb_mcp/: MCP server exposing debugging tools to AI agentsaidb_cli/: Developer CLI for testing, Docker, adapter buildsaidb_common/,aidb_logging/: Shared utilities and structured logging
For architecture details and implementation guidance, see the Developer Guide.
Robust Testing & Releases
AIDB is built with a comprehensive CI/CD pipeline:
- Thorough E2E Testing: Multi-language, multi-framework integration tests
- Automated Releases: Reliable version management and publishing
- Continuous Quality: The test suite is run nightly and on all release PRs
We catch issues early and ship features confidently, ensuring the debugging experience you depend on stays reliable.
Our entire CI/CD release pipeline executes start to finish in under 15 minutes––a target we plan to maintain.
Our Vision
Becoming the debugging standard in the MCP tools space.
As AI agents become more capable, they need debugging tools designed for their workflows—not adapted from human-centric IDEs. AIDB provides a unified, language-agnostic approach to debug any program with any AI agent through the proven MCP standard.
We're building the future of AI-assisted debugging, one DAP adapter at a time.
Contributing
We welcome contributions! See our Contributing Guide to get started.
- Contributing Guide - How to contribute
- Code of Conduct - Community standards
- Security Policy - Reporting vulnerabilities
Community & Support
- Documentation: ai-debugger.com
- Discord Community: Join the conversation
- Issues & Features: GitHub Issues
License
AI Debugger is licensed under the Apache 2.0 License. See LICENSE for details.
<div align="center">
Ready to bring debugging to your AI assistant?
Get Started | Read the Docs | Join Discord
</div>
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。