I still struggle to see how a MCP endpoint is easier for agents to work with compared with a REST endpoint and a skills.md file.

it's not easier for agents to work with. it's easier for organizations to work with.

for agents, they're essentially the same thing - remote endpoints, and instructions on how to call those endpoints. what MCP brings is centralized updating and distribution of the instructions, and a promise that the skill and the REST api won't be out of sync with each other.

the one thing that skill.md+REST doesn't solve is how you get that skill.md to somebody else's computer, and how you ship an update to somebody else's computer once they've got a copy of the skill. if that's a problem you need to solve, you can either start inventing skill.md distribution protocols, or you can just use MCP.

Not all agents have access to a sandbox/cli/code execution environment to run arbitrary api calls etc. MCP helps by essentially having another tool call without needing a sandbox. If you do have a sandbox, then might as well do codemode if you insist on mcp https://blog.cloudflare.com/code-mode/

Because it's a separate marketing term.

Instead of the CEO mandating that the API server has to be agent compatible (where who knows what that means), they can just say "our product has an MCP".

On a technical level, who knows what it actually is (is it actually the new stateless version, does it have all the endpoints, is the regular API more feature-rich, do I need those features for my workflow?, etc.). But at a surface-level, the intention is clearer, and lets other gears (like sales and marketing) keep spinning without getting bogged down in technical details.

At my company Parallel AI, I just built an extremely well documented openapi spec and then MCP builds from that. Complete alignment with UI/API/MCP so there is no extra work.

Are others doing this?

It seemed obvious to me, but I don't hear others saying it.

The model has zero awareness of MCP, it’s the harness’ job to talk to the MCP server and simply present the model with the tools just like any other tool. The only giveaway to the model about where the tools come from is the ‘mcp__’ prefix in the name

Companies got to release an MCP server for their product and tell their investors they were pivoting to be AI native.

I don't want to expose my API key to Claude. An stdio MCP server wrapping an API lets me hide it

Yep. I’ve found that having an endpoint that serves a well, documented openapi.yaml is very effective for agentic usage. The biggest difference is that you can break down a REST API into RPC-like chunks and save on some tokens if you break up the tools well. But pragmatically, I think saying “tell your agent to hit /api/v3/openapi.yaml” is quite useful

or a CLI

Me too, it is just another RPC endpoint, heck all of this kind of stuff could even be done with Sun RPC.