▲ | brazukadev a day ago | |||||||||||||||||||||||||||||||||||||||||||
It is funny most people discussing here does not understand MCP at all. Besides tools, MCP has resources, prompts, sampling, elicitation, roots and each one of them is useful when creating apps connected to LLMs. MCP is not only about MCP Servers, the host/client part is as important as the servers/tools. For example, nowadays most LLM clients are chatbots, but an MCP client could be a chess game or a project management app. > I know about resources and prompts but I've seen almost no evidence of people actually using them these are features that MCP clients should implement and unfortunately, most of them still don't. The same for elicitation and sampling. Prompts, for example, are mostly useful when you use sampling, then you can create an agent from an MCP server. | ||||||||||||||||||||||||||||||||||||||||||||
▲ | tptacek a day ago | parent [-] | |||||||||||||||||||||||||||||||||||||||||||
What can I do with MCP that I can't do with the function calling interface in the OpenAI Responses API? Besides, obviously, grafting function calls into agents I didn't write; we all understand that's the value prop of MCP. But you're suggesting it's more than that. Fill in the blanks for us. | ||||||||||||||||||||||||||||||||||||||||||||
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