Davidyz/VectorCode
A code repository indexing tool to supercharge your LLM experience.
Platform-specific configuration:
{
"mcpServers": {
"VectorCode": {
"command": "npx",
"args": [
"-y",
"VectorCode"
]
}
}
}Add the config above to .claude/settings.json under the mcpServers key.
[](https://codecov.io/github/Davidyz/VectorCode) [](https://github.com/Davidyz/VectorCode/actions/workflows/test_and_cov.yml) [](https://pypi.org/project/vectorcode/)
VectorCode is a code repository indexing tool. It helps you build better prompt for your coding LLMs by indexing and providing information about the code repository you're working on. This repository also contains the corresponding neovim plugin that provides a set of APIs for you to build or enhance AI plugins, and integrations for some of the popular plugins.
> [!NOTE] > This project is in beta quality and is undergoing rapid iterations. > I know there are plenty of rooms for improvements, and any help is welcomed.
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LLMs usually have very limited understanding about close-source projects, projects that are not well-known, and cutting edge developments that have not made it into releases. Their capabilities on these projects are quite limited. With VectorCode, you can easily (and programmatically) inject task-relevant context from the project into the prompt. This significantly improves the quality of the model output and reduce hallucination.
[](https://asciinema.org/a/8WP8QJHNAR9lEllZSSx3poLPD?t=3)
> [!NOTE] > The documentation on the main branch reflects the code on the latest commit. > To check for the documentation for the version you're using, you can [check out
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