Code2Prompt
Transforms complex codebases into structured summaries optimized for language models, enabling better code understanding for analy
Code2Prompt MCP server leverages the high-performance code2prompt-rs Rust library to analyze codebases and generate structured summaries optimized for AI consumption. It provides tools for extracting context from repositories with fine-grained control over file inclusion/exclusion patterns, formatting options, and token encoding. The server bridges the gap between code repositories and language models by transforming complex codebases into contextual prompts that help AI assistants better understand and work with code, making it particularly valuable for code analysis, documentation generation, and technical assistance workflows.
Source
Repository: https://github.com/odancona/code2prompt-mcp
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