Forge - GPU Kernel Optimization

Name: Forge - GPU Kernel Optimization
Author: RightNow-AI

@RightNow-AI

About Forge - GPU Kernel Optimization

Turn slow PyTorch into fast CUDA/Triton kernels. 32 parallel swarm agents optimize your code on real datacenter GPUs (B200, H200, H100, A100) with up to 14x speedup over torch.compile.

#gpu #cuda #triton #pytorch #optimization #kernel #machine-learning #deep-learning

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "forge": {
      "command": "npx",
      "args": [
        "-y",
        "@rightnow/forge-mcp-server"
      ]
    }
  }
}

Tools

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Overview

What is Forge - GPU Kernel Optimization?

Forge is an MCP server that optimizes PyTorch code into fast CUDA/Triton kernels using 32 parallel swarm agents. It is designed for AI developers and agents who want to accelerate GPU operations without manual kernel engineering. The server provides tools to optimize existing kernels, generate new ones from descriptions, and benchmark results on datacenter GPUs (B200, H200, H100, A100, L40S, T4).

How to use Forge - GPU Kernel Optimization?

Add the server to an MCP client (e.g., Claude) with the command claude mcp add forge-mcp -- npx -y @rightnow/forge-mcp-server. Authenticate via browser-based OAuth using the forge_auth tool, then call forge_optimize (to optimize PyTorch code) or forge_generate (to generate kernels from a description). Additional tools include forge_credits to check balance, forge_status to monitor jobs, forge_cancel to cancel jobs, and forge_sessions to list past sessions.