gauravvij137

Neo is a specialised AI/ML engineering agent that can be accessed via an MCP server inside Claude Code.

Claude code is great at software engineering but when it comes to iterative AI tasks that require long horizon experimentation and results may not come in one go, Claude limits exhaust very fast.

The crux is: We shouldn't let Claude babysit long AI workflows!

These tasks are inherently iterative and can consume hundreds of turns.

With Neo MCP, Claude Code becomes the orchestrator and Neo heavy-lifts complex AI tasks and provides direct status updates with execution logs to Claude running locally in your environment.

This way, Claude spends way less tokens and also Neo consumes upto 62% lower cost compared to direct Claude API usage, thus delivering outcomes as a combined team at way cheaper costs.

This has been our cheat code since last month and we think there is a lot of scope even now to further optimize and mature Neo.

We appreciate any feedback or thoughts from you.

They've come along pretty far now.

I remember when there was hype around GLM 5 reaching great heights on benchmarks but eventually failing on practical coding and reasoning tasks. I guess this time the hype is real.

is this different from accessing on Openrouter?

The data leaving AWS boundary kills this for any regulated workload. We've been running side-by-side evals of open models against Claude on private test suites, using Neo as the orchestration layer. Keeps everything in-house and gives us objective comparison data.