Code2prompt

Category: Repository Code Analysis MCP Servers
Tags: mcp, code-analysis, summarization, language-models

Overview

Code2prompt is an MCP server designed to generate contextual and structured summaries from complex codebases. It facilitates the integration of code repositories with language models, optimizing them for better understanding and analysis workflows by AI assistants.

Features

• MCP Server: Runs as an MCP server to handle code analysis requests.
• Contextual Prompt Generation: Produces contextual prompts from codebases, aiding AI and language models in comprehending code structure and content.
• Structured Summaries: Generates structured summaries to bridge code and AI language models, enhancing analysis workflows.
• Rust-Powered Analysis: Utilizes the high-performance code2prompt-rs Rust library for code analysis.
• Optimized for AI Consumption: Outputs are formatted to be directly usable by language models, improving the efficiency of code understanding tasks.
• Integration Ready: Can be used as part of automated workflows for code analysis and AI-assisted development.

Installation

• Uses Rye for dependency management.
• Dependencies specified in pyproject.toml.
• Installation instructions available in the repository documentation.

License

MIT License

Source

https://github.com/odancona/code2prompt-mcp

Pricing

No pricing information is provided; the project is open source under the MIT License.