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This week’s system design refresher:
MCP vs API: what’s the difference?
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TCP vs UDP
AI and Machine Learning (ML)
How Python Works
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MCP vs API: what’s the difference?
APIs have been the backbone of software-to-software communication for decades. Now, a new player — the Model Context Protocol (MCP) — is emerging as an AI-native protocol designed for agents, IDEs, and LLMs.
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API (Application Programming Interface):
Purpose: Enables software-to-software communication.
Discovery: Requires documentation.
Standardization: Varies — REST, GraphQL, gRPC, etc.
MCP (Model Context Protocol):
Purpose: Enables AI-native communication between clients (agents, IDEs, LLMs) and servers.
Discovery: Self-describing (no external docs needed).
Standardization: One uniform protocol for resources, tools, and prompts.
Over to you: Do you think MCP will complement APIs or eventually replace them in AI-driven systems?
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TCP vs UDP
Every time data moves across the internet, it chooses between accuracy and speed. That’s TCP vs UDP.
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TCP: Connection-oriented and reliable. It ensures ordered, duplicate-free delivery with flow and congestion control, making it ideal for web browsing, email, and file transfers.
UDP: Connectionless and lightweight. It sends packets without guarantees of delivery or order, but with minimal overhead. It is perfect for gaming, streaming, and real-time communication.
📘 A piece of knowledge each day: AI and Machine Learning (ML)
What is AI? What is ML? Are they the same thing? We will clear the common confusion in this post.
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AI and ML are often treated as if they are the same thing. They are not. AI is the bigger field. It is about creating programs that can sens