Scalene

About

Scalene-MCP transforms the powerful Scalene profiler into an LLM-friendly FastMCP server. It allows AI agents to gain deep insights into the performance of Python applications and their C/C++ components, encompassing detailed CPU, memory, and GPU usage. Designed for zero-friction integration with tools like GitHub Copilot and Claude Code, it translates complex profiling data into structured JSON, enabling LLMs to automatically detect project structure, find bottlenecks, analyze performance, and suggest optimizations without manual intervention.

Key Features

• Generate structured JSON output optimized for consumption by Large Language Models (LLMs).
• Profile Python scripts and code snippets with full Scalene capabilities for CPU, memory, and GPU.
• 1 GitHub stars
• Offers seamless integration with popular LLM agents and IDEs like GitHub Copilot, Claude Code, and Cursor.
• Compare performance profiles between different runs to detect regressions.
• Analyze profiles to identify hotspots, bottlenecks, memory leaks, and performance recommendations.

Use Cases

• Automatically identify performance bottlenecks and resource-intensive sections in Python code using LLM agents.
• Receive AI-generated optimization suggestions based on detailed CPU, memory, and GPU profiling data.
• Streamline performance monitoring and regression detection by comparing code profiles across development cycles.