Local Code Indexing for Cursor

what is Local Code Indexing for Cursor?

Local Code Indexing for Cursor is an experimental Python-based server that locally indexes codebases using ChromaDB and provides a semantic search tool via an MCP (Model Context Protocol) server for tools like Cursor.

how to use Local Code Indexing for Cursor?

To use this project, clone the repository, set up your environment variables, start the indexing server using Docker, and configure Cursor to use the local search server.

key features of Local Code Indexing for Cursor?

• Local indexing of codebases using ChromaDB
• Semantic search capabilities for code
• Integration with Cursor IDE for enhanced code navigation

use cases of Local Code Indexing for Cursor?

1. Indexing multiple project folders for efficient code search.
2. Enhancing code navigation in Cursor IDE with semantic search.
3. Facilitating quick access to code functionalities through local vector searches.

FAQ from Local Code Indexing for Cursor?

• What is ChromaDB?

ChromaDB is a database designed for managing and querying vector embeddings, which is used for semantic search.

• How do I configure the projects to index?

You can specify the projects to index in the .env file under the FOLDERS_TO_INDEX variable.

• Is this project suitable for large codebases?

Yes, it is designed to handle multiple projects and can be optimized for larger codebases.