The @withneo MCP server makes Claude Code, Codex, Cursor, and any other agentic coding system dramatically more efficient on AI/ML engineering tasks.

In the experiment we ran, using the MCP server ran 37% faster and produced a cleaner, more structured benchmarking pipeline.

The difference was approach.

Claude Code jumped straight to implementation using the standard libraries and design patterns most projects default to.

Neo, however, first researched the problem, selected the right libraries for this specific workload, and designed around performance from the start.

General-purpose agents become much more powerful when they can call specialized engineering agents.

You should take a look at the NEO MCP if you are trying to run evals, fine-tune models, inference benchmarking, or any other engineering workflow.

Here is the link to try it: https://heyneo.so/signup?campaign_name=svpinomcp

And here is the complete case study if you want to read more about these results: https://heyneo.com/claude-code

Thanks to the NEO team for partnering with me on this post.