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Stop letting your AI repeat mistakes: I built an open-source MCP observability dashboard (React 19 + ECharts) 🚀

Vibe coding with tools like Claude Code or Cursor feels like magic—until your AI repeats the exact same bug it made 10 minutes ago. As developers, we are d…

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Vibe coding with tools like Claude Code or Cursor feels like magic—until your AI repeats the exact same bug it made 10 minutes ago.



As developers, we are dealing with two massive pain points in AI-assisted development right now:



The Black Box: We have no idea how many tokens we are burning or where the time actually goes.



AI Amnesia: You correct the AI, but in the next session, it forgets everything and breaks your codebase again.



To solve this, I built ai-dev-analytics (AIDA).



Meet AIDA 🕵️‍♂️

AIDA is an open-source, 100% local Model Context Protocol (MCP) server that acts as an observability layer for your AI sessions.





Instead of just being a "token counter," AIDA is a Rule Auto-Codifier.



✨ The Killer Feature

When AIDA detects that the AI has gone off-track or introduced an architectural deviation, it doesn't just log it. It automatically distills that failure into persistent project rules (compatible with .cursorrules or .clauderules).



Your AI actually learns from its failures and stops repeating them.



🛠️ The Tech Stack

As a web frontend developer, I wanted the dashboard to be modern, fast, and beautiful:



Dashboard: Built from scratch with React 19, Tailwind CSS 4, and ECharts for real-time ROI and bottleneck visualizations.



Runtime: Node.js + TypeScript.



Security: 100% Local. Zero runtime dependencies. Verified A/A/A Score on Glama.ai.









⚡ Quick Start (Zero Config)

You don't need to clone the repo or install heavy dependencies. Just add this single line to your MCP client config:




{
"mcpServers": {
"aida": {
"command": "npx",
"args": ["-y", "ai-dev-analytics", "mcp"]
}
}
}






🤝 Let's build together

I just released v1.0.0 today. If you are tired of AI amnesia and want to make your vibe coding measurable, give it a try!



🔗 GitHub Repository: https://github.com/LWTlong/ai-dev-analytics



Drop a ⭐ if it helps your workflow, and let me know your thoughts in the comments! What's the most annoying mistake your AI keeps repeating?

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