ai-spark-mcp-server

ai-spark-mcp-server

8
developer_toolscloud_platforms

Spark MCP Optimizer enables the optimization of Apache Spark code through an MCP server and client architecture utilizing Claude AI for enhanced performance analysis and suggestions. It streamlines intelligent code optimization and performance insight generation for PySpark applications.

Spark MCP (Model Context Protocol) Optimizer

This project implements an MCP server and client for optimizing Apache Spark code. It provides intelligent code optimization suggestions and performance analysis through a client-server architecture.

How It Works

  • Input Layer: Submission of PySpark code for optimization and performance analysis.
  • MCP Client and Server: Facilitates communication, handles protocol requests, and manages tool execution.
  • Resources: Utilizes Claude AI for code analysis.
  • Output Layer: Generates optimized code and performance analysis reports.

Usage

  • Requirements: Python 3.8+, PySpark 3.2.0+, Anthropic API Key.
  • Installation: pip install -r requirements.txt
  • Start Workflow:
    1. Add Spark code in input/spark_code_input.py.
    2. Start server with python v1/run_server.py.
    3. Run client with python v1/run_client.py.
    4. Compare code performance with python v1/run_optimized.py.

Features

  • Intelligent code optimization using Claude AI.
  • Comprehensive performance analysis of original vs. optimized code.
  • Simple integration with MCP architecture.
  • Auto-generated optimized code with detailed comments.