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    Cursor Local Indexing

    ChromaDB-powered local indexing support for Cursor, exposed as an MCP server

    24 stars
    Python
    Updated Sep 13, 2025

    Documentation

    Local Code Indexing for Cursor

    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.

    Setup

    1. Clone and enter the repository:

    bash
    git clone 
       cd cursor-local-indexing

    2. Create a .env file by copying .env.example:

    bash
    cp .env.example .env

    3. Configure your .env file:

    env
    PROJECTS_ROOT=~/your/projects/root    # Path to your projects directory
       FOLDERS_TO_INDEX=project1,project2    # Comma-separated list of folders to index

    Example:

    env
    PROJECTS_ROOT=~/projects
       FOLDERS_TO_INDEX=project1,project2

    4. Start the indexing server:

    bash
    docker-compose up -d

    5. Configure Cursor to use the local search server:

    Create or edit ~/.cursor/mcp.json:

    json
    {
         "mcpServers": {
           "workspace-code-search": {
             "url": "http://localhost:8978/sse"
           }
         }
       }

    6. Restart Cursor IDE to apply the changes.

    The server will start indexing your specified projects, and you'll be able to use semantic code search within Cursor when those projects are active.

    7. Open a project that you configured as indexed.

    Create a .cursorrules file and add the following:

    code
    For any request, use the @search_code tool to check what the code does.
    Prefer that first before resorting to command line grepping etc.

    8. Start using the Cursor Agent mode and see it doing local vector searches!

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