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.

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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

MCP Servers Are Becoming the UI for AI Agents

Agentic Conversations (formally mlops.community)

MCP Servers Are Becoming the UI for AI Agents