Pypreader
Enables AI models to inspect the contents and source code of Python packages within a specified environment.
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Pypreader acts as a crucial bridge between AI models and local Python environments, addressing the common challenge of LLMs lacking awareness of third-party libraries. By implementing the Model Context Protocol, it empowers AI-integrated IDEs like Cursor and Trae to programmatically browse installed packages, view their file structure, read source code, and fetch official PyPI descriptions. This direct access to contextual information helps AI agents overcome hallucinations and accurately understand dependencies, facilitating more effective code analysis, dependency inspection, and automated programming assistance.
Características Principales
- List file and directory structures of installed Python packages
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- Retrieve full source code of specific files within a package
- Fetch official package descriptions from PyPI
Casos de Uso
- Enabling intelligent dependency inspection for automated programming assistance
- Enhancing AI-integrated development environments with contextual library information
- Facilitating accurate code analysis by AI agents