MCP Sheet 1

📗 MCP Fundamentals - Quiz 1

#	Question	Answer
Q1	What is the primary purpose of Model Context Protocol (MCP)?	B) To enable AI models to connect with external data sources, tools, and environments
Q2	What problem does MCP primarily aim to solve?	C) The M×N Integration Problem
Q3	Which of the following is a key benefit of MCP?	C) Standardization and interoperability in the AI ecosystem
Q4	In MCP terminology, what is a "Host"?	B) The user-facing AI application
Q5	What does "M×N Integration Problem" refer to in the context of AI applications?	B) The challenge of connecting M AI applications to N external tools without a standard

Q1: What does the 'P' in MCP stand for?

Protocol - Model Context Protocol.

Q2: What problem does MCP solve?

The M×N problem - Too many connections between AI apps and tools.

Q3: Where does MCP fit in?

Between the AI model and external tools as a middleware layer.

Q4: Was MCP developed by Anthropic, and can other models use it?

Yes - MCP was developed by Anthropic. It's an open standard, so any AI model can use it.

Q5: What is the difference between MCP and function calling?

Function calling is built into a specific model, while MCP is a standard that works with any model.

Q6: How does MCP differ from previous OpenAI plugins?

Q7: What is the difference between MCP and GPTs?

Q8: Will MCP become a standard?

Very likely, because big companies are already using it.

Q9: Should we adopt MCP?

Yes, if you need AI to connect with external tools.

Q10: Will domestic internet platforms adopt MCP?

Maybe. It depends on each platform's needs.

Q11: Is MCP suitable for agents?

MCP is not designed for agents; it is designed for models to connect to external tools.

Q12: What is MCP?

A protocol that lets AI connect to external tools and data.

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