Comment by fnordpiglet
17 hours ago
One advantage is the MCP advertises itself to the agent with its schema and api shape. Unless your CLI is in the corpus with lots of examples the agent has to learn every time. Skills help a little bit but I find the recall on skills pretty low. However I also find codex will reliably use MCPs advertised while Claude always reaches for tools like Bash() likely because it’s aligned so heavily on its own tools and is very hard to get to use an MCP if literally any Bash() approach is possible, including breaking glass to find creds, even when an MCP is clearly advertised in CLAUDE.md, skills, and explicit user instruction. I find it fascinating that Anthropic makes a product that seems to be really poor at following instructions and OpenAI seems to generally follow guard rails.
Isn’t that basically just a —help flag though?
Still easily doable with CLI
> Isn’t that basically just a --help flag though?
mostly, but not enough — i have been experimenting with this, and what i found to help is:
Then give the CLI a man page.
> One advantage is the MCP advertises itself to the agent with its schema and api shape.
So, OpenAPI/Swagger for REST? GraphQL? SOAP schemas? All of these (and more) exist. What does MCP add that these don't have?
i mean you can surface an openapi schema too.
MCP is more than is more than tools. Tools is one of three major features: prompts[0] and resources[1] being the other two.
Prompts are effectively "server delivered skills" which are are quite powerful because it solves a distribution and synchronization problem. It also allows server materialization and dynamic construction of skills.
MCP also has a few other under utilized mechanisms: elicitation[2] on the client side and completions on the server side[3]. It is an API of sorts, but specialized for agent harness <-> server interactions.
[0] https://modelcontextprotocol.info/docs/concepts/prompts/
[1] https://modelcontextprotocol.info/docs/concepts/resources/
[2] https://modelcontextprotocol.io/specification/2025-11-25/cli...
[3] https://modelcontextprotocol.io/specification/2025-11-25/ser...
this is bad. Anyone doing any cursory work with agents will realize how brittle <<just managing your own prompts>> can be. Adding an extra layer of indirection isn’t helpful, it’s a gigantic hindrance that gives you a moving eval target. Being an MCP developer means you have a moving target of model optimization. It is a win for nobody.
The tools we need to solve this problem exist and they are boring. Types, jsonschema, openapi, all of it is a better integration point than MCP.
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can these not be surfaced in an api and accessed using curl, with instructions in a SKILLS.md?
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