Show Notes
Naseem Al-Naji is the co-founder of MCPcat.io and the creator of Opal — a builder with deep roots in privacy-first developer tooling. In this conversation, he breaks down why MCP servers have become a black box in production, and how MCPcat gives teams X-ray vision into how agents and users actually behave.
What we get into: 🐱 What MCPcat Is — Open-source analytics and live debugging built specifically for MCP servers 🎬 Session Replay — Watch an agent's full journey through your server, tool call by tool call 🎯 Agent Intent & Goals — Understand "why" a tool was called, not just that it was 🔍 Trace Debugging — Find exactly where agents and users get stuck or confused 🚨 Catching Hallucinations — How issue tracking surfaces when an LLM goes off the rails 🔒 Privacy-First by Design — Client-side redaction so sensitive data never leaves your environment ⚡ One-Line Integration — Python, TypeScript, and Go SDKs that drop into existing stacks 📊 Works With Your Stack — Native support for OpenTelemetry, Datadog, and Sentry 🚀 The Future of MCP — Where agent observability and the MCP ecosystem are heading
If you build, ship, or maintain MCP servers — or you're trying to figure out why your AI agents misbehave in production — this one's for you.
🔔 Subscribe, like, and share for more conversations on agentic AI: ▶️ YouTube: https://www.youtube.com/@AAIFAgenticConversations🎧 Spotify: https://open.spotify.com/show/033rZZJrQOVSSmhcStFhZA?si=rUNjFuNqRvGvAEWwqms7TA
Links & Resources: 🐱 MCPcat: https://mcpcat.io 💻 MCPcat on GitHub: https://github.com/mcpcat 👤 Naseem on LinkedIn: https://www.linkedin.com/in/naseem-al-naji 🐙 Naseem on GitHub: https://github.com/naji247
Timestamps: [00:00] Intro [01:41] MCP Needs Gatekeepers [06:32] Measuring MCP Success [13:57] MCPAT Feature Rollouts [18:50] MCP Server Query Optimization [26:48] UI Design Shift [29:14] MCP Server Design Choices [33:51] User Journey Traceability [40:40] Agent Experience Evaluation [45:23] AI Model Improvement Strategies
#MCP #AIAgents #Observability
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