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This playbook installs the DGX Spark MCP Server, a tool for hardware-aware Spark optimization on DGX systems. Includes: - Installation script (npm based) - Systemd service configuration - Default configuration - Documentation
85 lines
2.2 KiB
Markdown
85 lines
2.2 KiB
Markdown
# DGX Spark MCP Server Playbook
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This playbook installs and configures the **DGX Spark MCP Server**, a tool that provides hardware-aware Apache Spark optimization for NVIDIA DGX systems via the Model Context Protocol (MCP).
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## Overview
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The DGX Spark MCP Server enables MCP clients (like Claude Desktop or Claude Code) to:
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* **Detect Hardware**: Automatically read DGX GPU topology, memory, and CPU specs.
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* **Optimize Spark**: Generate tuned Spark configurations (`spark-submit` args) based on detected hardware and workload type (ETL, ML Training, Inference).
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* **Monitor**: Check real-time GPU availability before submitting jobs.
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## Prerequisites
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* **NVIDIA DGX System** (or compatible GPU server)
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* **NVIDIA Drivers** installed (`nvidia-smi` available)
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* **Node.js 18+**
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* **Root access** (for systemd service installation)
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## Directory Structure
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```
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.
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├── config/
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│ └── default.json # Default configuration
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├── deploy/
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│ └── dgx-spark-mcp.service # Systemd service file
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└── scripts/
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└── install.sh # Automated installer
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```
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## Installation
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1. **Run the installer**:
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```bash
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sudo ./scripts/install.sh
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```
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This script will:
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* Install `dgx-spark-mcp` globally via `npm`.
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* Create a dedicated system user (`dgx`).
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* Setup logging directory `/var/log/dgx-spark-mcp`.
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* Install and start the systemd service.
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2. **Verify Installation**:
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```bash
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systemctl status dgx-spark-mcp
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```
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## Configuration
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The configuration file is located at `/etc/dgx-spark-mcp/config.json`.
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### Key Settings
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* **`mcp.transport`**: `stdio` (default) or `sse`.
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* **`hardware.enableGpuMonitoring`**: Set to `true` to enable real-time `nvidia-smi` queries.
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* **`logging.level`**: `info` or `debug`.
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## Usage with Claude Desktop
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Add the following to your `claude_desktop_config.json`:
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```json
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{
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"mcpServers": {
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"dgx-spark": {
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"command": "dgx-spark-mcp"
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}
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}
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}
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```
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## Troubleshooting
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**Service fails to start?**
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Check logs:
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```bash
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journalctl -u dgx-spark-mcp -f
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```
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**Permission denied?**
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Ensure the `dgx` user has permissions to access `nvidia-smi`. You may need to add the user to the `video` group:
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```bash
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usermod -a -G video dgx
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```
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