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[ARTICLE · art-34099] src=heyneo.com ↗ pub= topic=ai-tools verified=true sentiment=↑ positive

Extend Claude limits by offloading AI tasks to Neo

Neo launched an MCP server that lets users offload AI tasks from Claude, reducing costs by 62% and speeding up runtime by 37% in benchmarks. The tool integrates with Claude Code and other MCP clients, choosing optimized backends like ONNX Runtime over PyTorch for CPU-only environments.

read1 min views1 publishedJun 19, 2026

Add NEO's MCP server to any environment with Python 3.11+.

Open your NEO dashboard, create a key, and copy it. Keys look like sk-v1-….

Register NEO with one command, then just ask in a new chat to ship work.

claude mcp add --scope user neo \
  -e NEO_SECRET_KEY=sk-v1-your-key \
  -- python3 -m neo_mcp

Using Cursor, VS Code, or another MCP client? See the neo-mcp setup.

Independent benchmark

The task: benchmark a speech-to-text model on a CPU-only Azure VM — 2 cores, 7.7 GB RAM, no GPU. Claude Code alone reached for the obvious HuggingFace + PyTorch path and iterated in real time. NEO spent two minutes researching first, then chose ONNX Runtime for its AVX2-optimized CPU kernels — same task, same machine.

Cost per task

$1.96$0.74

62% cheaper

Runtime (RTF)

0.5190.328

37% faster

Backend chosen

PyTorchONNX Runtime

CPU-optimized

Benchmark by Gaurav Vij · Read the full writeup

Install once, then delegate ML work to NEO from any Claude Code session.

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