
Sign up to save your podcasts
Or


Naseem Al-Naji is the co-founder of MCPcat.io and the creator of Opal β 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:
π± What MCPcat Is β Open-source analytics and live debugging built specifically for MCP servers
π¬ Session Replay β Watch an agent's full journey through your server, tool call by tool call
π― Agent Intent & Goals β Understand "why" a tool was called, not just that it was
π Trace Debugging β Find exactly where agents and users get stuck or confused
π¨ Catching Hallucinations β How issue tracking surfaces when an LLM goes off the rails
π Privacy-First by Design β Client-side redaction so sensitive data never leaves your environment
β‘ One-Line Integration β Python, TypeScript, and Go SDKs that drop into existing stacks
π Works With Your Stack β Native support for OpenTelemetry, Datadog, and Sentry
π The Future of MCP β Where agent observability and the MCP ecosystem are heading
If you build, ship, or maintain MCP servers β or you're trying to figure out why your AI agents misbehave in production β this one's for you.
π Subscribe, like, and share for more conversations on agentic AI:
βΆοΈ YouTube: https://www.youtube.com/@AAIFAgenticConversationsπ§ Spotify: https://open.spotify.com/show/033rZZJrQOVSSmhcStFhZA?si=rUNjFuNqRvGvAEWwqms7TA
Links & Resources:
π± MCPcat: https://mcpcat.io
π» MCPcat on GitHub: https://github.com/mcpcat
π€ Naseem on LinkedIn: https://www.linkedin.com/in/naseem-al-naji
π 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
By Demetrios4.6
2323 ratings
Naseem Al-Naji is the co-founder of MCPcat.io and the creator of Opal β 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:
π± What MCPcat Is β Open-source analytics and live debugging built specifically for MCP servers
π¬ Session Replay β Watch an agent's full journey through your server, tool call by tool call
π― Agent Intent & Goals β Understand "why" a tool was called, not just that it was
π Trace Debugging β Find exactly where agents and users get stuck or confused
π¨ Catching Hallucinations β How issue tracking surfaces when an LLM goes off the rails
π Privacy-First by Design β Client-side redaction so sensitive data never leaves your environment
β‘ One-Line Integration β Python, TypeScript, and Go SDKs that drop into existing stacks
π Works With Your Stack β Native support for OpenTelemetry, Datadog, and Sentry
π The Future of MCP β Where agent observability and the MCP ecosystem are heading
If you build, ship, or maintain MCP servers β or you're trying to figure out why your AI agents misbehave in production β this one's for you.
π Subscribe, like, and share for more conversations on agentic AI:
βΆοΈ YouTube: https://www.youtube.com/@AAIFAgenticConversationsπ§ Spotify: https://open.spotify.com/show/033rZZJrQOVSSmhcStFhZA?si=rUNjFuNqRvGvAEWwqms7TA
Links & Resources:
π± MCPcat: https://mcpcat.io
π» MCPcat on GitHub: https://github.com/mcpcat
π€ Naseem on LinkedIn: https://www.linkedin.com/in/naseem-al-naji
π 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

1,292 Listeners

288 Listeners

1,095 Listeners

624 Listeners

583 Listeners

301 Listeners

345 Listeners

213 Listeners

563 Listeners

507 Listeners

146 Listeners

100 Listeners

227 Listeners

689 Listeners

32 Listeners