What is mcp-debugging-enhanced?

A troubleshooting guide for MCP servers, which provide tools that AI assistants can call. It covers server health, configuration, network connections, protocol messages, performance, logs, and selected automatic fixes.

Use it to diagnose failed connections, timeouts, invalid settings, protocol errors, slow responses, resource problems, or MCP logs.

It helps identify whether an MCP failure comes from the server, network, configuration, compatibility, or resource usage.

mcp-debugging-enhanced — Cursor rule by Mr-chen-05

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods

npx agentmods add rules/mr-chen-05/rules-2.1-optimized/mcp-debugging-enhanced

Clone the repo

git clone --depth 1 https://github.com/Mr-chen-05/rules-2.1-optimized

Per session 3,814 This file is loaded in full into every session.

When invoked 3,814 The same file — it is already loaded in full.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5	$0.03814	$0.03814
Opus 5	$0.01907	$0.01907
Sonnet 5	$0.00763	$0.00763
Haiku 4.5	$0.00381	$0.00381

Measured 3d ago against content hash e318425da2ac, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

mcp-debugging-enhanced scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

project-rules/mcp-debugging-enhanced.mdc · 485 lines

How it starts

The opening of the file, as written. The whole thing — 485 lines — stays where its author put it; the contents beside it link to each section on GitHub.

🔧 MCP Debugging Enhanced - 增强MCP调试工具

AI驱动的MCP服务器调试和诊断系统，提供智能故障分析、性能监控和自动化修复建议。

🧠 AI Intelligence Core - AI智能核心

智能激活条件

自动激活场景:
  - 检测到MCP工具连接失败或异常
  - 用户执行 "/mcp-debug" 命令
  - systematic-debugging触发MCP相关调试
  - MCP工具性能异常或超时
  - 超级大脑系统推荐MCP诊断

智能分析维度:
  - MCP服务器状态和健康度 (35%)
  - 网络连接和通信质量 (25%)
  - 配置正确性和兼容性 (20%)
  - 性能指标和资源使用 (15%)
  - 错误模式和历史问题 (5%)

🚀 Commands - 智能命令

/mcp-debug - AI智能MCP调试（推荐）
/mcp-debug --health - MCP健康度检查
/mcp-debug --performance - MCP性能分析
/mcp-debug --config - MCP配置诊断
/mcp-debug --network - 网络连接诊断
/mcp-debug --logs - MCP日志分析
/mcp-debug --fix - 自动修复MCP问题

✨ AI-Powered Features - AI驱动功能

🤖 智能MCP诊断引擎

MCP服务器分析:
  状态检测:
    - 服务器运行状态
    - 进程健康度检查
    - 内存和CPU使用
    - 网络端口状态

  配置分析:
    - MCP配置文件验证
    - 环境变量检查
    - 依赖关系分析
    - 版本兼容性检查

  性能监控:
    - 响应时间监控
    - 吞吐量分析
    - 资源使用统计
    - 错误率监控

  通信诊断:
    - 协议兼容性检查
    - 消息格式验证
    - 数据传输质量
    - 连接稳定性分析

智能故障识别:
  - 常见故障模式识别
  - 异常行为检测
  - 性能瓶颈定位
  - 配置错误识别

🔧 自动化修复引擎

可自动修复的问题:
  配置问题:
    - 端口冲突解决
    - 环境变量修复
    - 路径配置纠正
    - 权限问题修复

  连接问题:
    - 网络连接重试
    - 超时参数调整
    - 协议版本协商
    - 认证配置修复

  性能问题:
    - 缓存配置优化
    - 连接池调整
    - 内存使用优化
    - 并发参数调整

修复策略:
  - 渐进式修复方法
  - 影响最小化原则
  - 自动备份和回滚
  - 修复效果验证

📊 智能监控和分析

实时监控:
  - MCP服务器状态监控
  - 性能指标实时追踪
  - 错误和异常监控
  - 资源使用监控

历史分析:
  - 性能趋势分析
  - 错误模式识别
  - 使用统计分析
  - 优化效果评估

预测分析:
  - 故障风险预测
  - 性能瓶颈预警
  - 资源需求预测
  - 维护时机建议

🔄 AI Workflow Process - AI工作流程

Phase 1: 诊断扫描阶段

Step 1 - 环境检测:
  - 扫描所有已安装的MCP工具
  - 检查MCP服务器运行状态
  - 分析MCP配置文件
  - 验证环境变量和依赖

Step 2 - 连接测试:
  - 测试MCP服务器连接
  - 验证通信协议
  - 检查认证和权限
  - 测试基本功能调用

Step 3 - 性能基准:
  - 测量响应时间
  - 评估吞吐量
  - 监控资源使用
  - 建立性能基线

Phase 2: 深度分析阶段

Step 4 - 故障分析:
  - 分析错误日志和堆栈
  - 识别故障模式和原因
  - 评估故障影响范围
  - 生成故障分析报告

Step 5 - 性能分析:
  - 识别性能瓶颈
  - 分析资源使用模式
  - 评估优化机会
  - 生成性能分析报告

Step 6 - 配置分析:
  - 验证配置正确性
  - 识别配置冲突
  - 分析最佳实践偏离
  - 生成配置优化建议

Phase 3: 修复优化阶段

Step 7 - 自动修复:
  - 执行可自动修复的问题
  - 应用配置优化建议
  - 实施性能优化措施
  - 验证修复效果

Step 8 - 监控设置:
  - 建立持续监控机制
  - 配置预警和通知
  - 设置性能基准监控
  - 启用自动化维护

Read the full file on GitHub · 485 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

3d ago First seen · 485 lines · 3,814 tokens per session scan A e318425da2ac

Subscribe to this mod's changes

mcp-debugging-enhanced is a cursor rule published in the GitHub repository Mr-chen-05/rules-2.1-optimized (172 stars, last pushed 9mo ago), licensed MIT. It adds 3,814 tokens to every session, about $0.0191 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Debugging

mcp-debugging-enhanced