VectorCode

What is VectorCode? VectorCode is a code repository indexing tool designed to enhance the experience of using large language models (LLMs) by indexing and providing contextual information about the code repositories you are working on. How to use VectorCode? To use VectorCode, you can install the command-line tool or the Neovim plugin. Follow the setup instructions in the documentation to get started with indexing your code repositories and utilizing the features of the tool. Key features of VectorCode? Indexing of code repositories for better context in LLM prompts. Integration with Neovim for seamless coding experience. Support for multiple embedding engines through Chromadb. Basic retrieval and embedding functionalities with room for improvements. Use cases of VectorCode? Enhancing code completion suggestions in LLMs for less-known or closed-source projects. Assisting developers in writing better prompts for AI coding assistants. Providing contextual information for complex coding tasks. FAQ from VectorCode? What is the purpose of VectorCode? VectorCode aims to improve the understanding of LLMs regarding code repositories, especially those that are not well-known or closed-source. Is VectorCode free to use? Yes! VectorCode is open-source and free to use. What programming languages does VectorCode support? VectorCode is primarily developed in Python and supports various programming languages through its indexing capabilities.

As an MCP (Model Context Protocol) server, VectorCode enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.

To use VectorCode, you can install the command-line tool or the Neovim plugin. Follow the setup instructions in the documentation to get started with indexing your code repositories and utilizing the features of the tool. Key features of VectorCode? Indexing of code repositories for better context in LLM prompts. Integration with Neovim for seamless coding experience. Support for multiple embedding engines through Chromadb. Basic retrieval and embedding functionalities with room for improvements. Use cases of VectorCode? Enhancing code completion suggestions in LLMs for less-known or closed-source projects. Assisting developers in writing better prompts for AI coding assistants. Providing contextual information for complex coding tasks. FAQ from VectorCode? What is the purpose of VectorCode? VectorCode aims to improve the understanding of LLMs regarding code repositories, especially those that are not well-known or closed-source. Is VectorCode free to use? Yes! VectorCode is open-source and free to use. What programming languages does VectorCode support? VectorCode is primarily developed in Python and supports various programming languages through its indexing capabilities.

Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.