Provides call graph analysis capabilities to LLMs through a Model Context Protocol (MCP) server.
This Model Context Protocol (MCP) server empowers Large Language Models (LLMs) to deeply understand code structure by providing access to function call graphs. Through standardized tools and resources, AI assistants can initialize and explore call graphs for Python repositories, analyze function dependencies, and ultimately deliver more contextually aware and accurate code assistance.
Características Principales
01Initialize call graphs for Python repositories
02Explore function call relationships
03Analyze dependencies between functions
04Analyze impact of code changes
05Provides a function analysis prompt
Casos de Uso
01Enhance code completion and suggestion accuracy in LLM-powered IDEs.
02Improve the ability of AI assistants to answer code-related questions.
03Automate code review processes by identifying potential issues based on dependency analysis.
