MCPs are deterministic, SKILLS.md isn't. Also run.js can run arbitrarily generated Node.js code. It is a trivial vector for command injection.
This might be sufficient for an independent contractor or student. It shouldn't be used in a production agent.
> MCPs are deterministic, SKILLS.md isn't.
MCPs themselves may provide access to tools that are either deterministic or not, but the LLM using them generally isn't deterministic, so when used by an LLM as part of the request-response cycle determinism, if the MCP-provided tool had it, is not in a feature of the overall system.
SKILLS.md relies on a deterministic code execution environment, but has the same issue. I'm not seeing a broad difference in kind here when used in the context of an LLM response generation cycle, and that’s really the only context where both are usable (MCP could be used for non-LLM integration, but that doesn't seem relevant.)
LLMs are not deterministic though. So by definition MCPs are not deterministic.
For example, GPT-5 doesn't support temperature parameter. And even models that do support temperature are not deterministic with temperature=0.
Yeah, this isn’t meant to replace your real tests it’s more for quick “does my new feature work?” checks during local dev. Think of it like scriptable manual testing: Claude spits out the Playwright code faster than you would, but it’s not CI-level coverage.
And for privacy screenshots stay local in /tmp, but console output and page content do go to Claude/Anthropic. It’s designed for dev environments with dummy data, not prod. Same deal as using Claude for any coding help.
If you're going to use claude to help you respond to feedback the least you can do is restate this in your own words. Parent commenter deserves the respect of corresponding with a real human being.
You don’t understand what you’re talking about enough so you have to ask llm to generate a response for you?
MCPs aren't deterministic...
Yes, they are. Like any standard API, it is an orchestration layer that, given a specific input should always execute the same logic and produce a consistent output. Its job is deterministic execution.
The agentic system that uses MCP (e.g., an LLM) is fundamentally non-deterministic. The LLM's decision of which tool to call, when to call it, and what to do with the response is stochastic.