An MCP server that decodes V8 CPU profiles into token-efficient bottleneck summaries for AI agents, enabling them to analyze CPU consumption, call trees, GC pressure, and async bottlenecks.
An MCP server that detects energy anti-patterns in Python code, retrieves optimization examples, suggests refactoring, validates correctness, and benchmarks resource gains, integrating with VS Code, Cursor, and Windsurf.
FastMCP is a comprehensive MCP server allowing secure and standardized data and functionality exposure to LLM applications, offering resources, tools, and prompt management for efficient LLM interactions.
A server that provides Model Control Protocol (MCP) tools for High Performance Computing, designed to integrate with Large Language Models in IDEs like Cursor and VSCode for debugging and other HPC tasks.
An MCP server that enables LLMs to understand and analyze code structure through function call graphs, allowing AI assistants to explore relationships between functions and analyze dependencies in Python repositories.