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.

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 /neo-mcp . 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 https://medium.com/@gauravvij/claude-code-an-ai-agent-cut-my-ai-engineering-costs-by-62-claude-code-alone-couldnt-840c6e8502e9 Install once, then delegate ML work to NEO from any Claude Code session.