flow-nexus-neuralsolid

# Flow Nexus Neural Networks Deploy, train, and manage neural networks in distributed E2B sandbox environments. Train custom models with multiple architectures (feedforward, LSTM, GAN, transformer) or use pre-built templates from the marketplace. ## Prerequisites ```bash # Add Flow Nexus MCP server claude mcp add flow-nexus npx flow-nexus@latest mcp start # Register and login npx flow-nexus@latest register npx flow-nexus@latest login ``` ## Core Capabilities ### 1. Single-Node Neural Training Train neural networks with custom architectures and configurations. **Available Architectures:** - `feedforward` - Standard fully-connected networks - `lstm` - Long Short-Term Memory for sequences - `gan` - Generative Adversarial Networks - `autoencoder` - Dimensionality reduction - `transformer` - Attention-based models **Training Tiers:** - `nano` - Minimal resources (fast, limited) - `mini` - Small models - `small` - Standard models - `medium` - Complex models - `large` - Large-scale training #### Example: Train Custom Classifier ```javascript mcp__flow-nexus__neural_train({ config: { architecture: { type: "feedforward", layers: [ { type: "dense", units: 256, activation: "relu" }, { type: "dropout", rate: 0.3 }, { type: "dense", units: 128, activation: "relu" }, { type: "dropout", rate: 0.2 }, { type: "dense", units: 64, activation: "relu" }, { type: "dense", units: 10, activation: "softmax" } ] },