Comment by brazukadev

> MCPs are interpreters of those function calls.

No, tool calls are just one of many MCP parts. People thinking MCP = SOAP or DCOM or JSON-RPC or OpenAPI didn't stop 20 minutes to read and understand MCP.

Tool calls is 20% of MCP, at maximum. And a good amount of it is dynamically generating the tool list exposed to LLMs. But lots of people here think MCP === give the model 50 tools to choose from

simonw 2 days ago

"Tool calls is 20% of MCP, at maximum"

What else is there? I know about resources and prompts but I've seen almost no evidence of people actually using them, as far as I can tell tools are 90% of the usage of MCP, if not more.

brazukadev OP 2 days 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 2 days ago

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.

didibus 2 days ago

The MCP can expose a list of tools, but also a list of prompt templates, a list of resources, it can ask the client to run something through the LLM (called sampling), and it can provide rules for when to follow up with questions.

But you can do all that yourself if you're building your own agent and directly calling a model. But if you want to be able to provide behavior to any agent, that's where MCP comes in.

brazukadev OP 2 days ago

The LLM can only use MCP tools, but the Client you use the model can access resources, prompts, elicitation and sampling, which are tools to help with querying the model. So one MCP server that implements some or all these features can act as an agent for the LLM dispatching tasks IF the client is also an MCP host/client.