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Local RAG

Local RAG for semantic document search without external API calls.

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Updated Nov 4, 2025
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Local RAG for semantic document search without external API calls.
  1. Determine the Folder for Your Documents
    Decide which folder on your computer contains the documents you want to search through. This folder will be referenced as BASE_DIR and the server will only have access to files within this directory.

  2. Open the FastMCP Connection Interface
    Go to the FastMCP connection interface and locate your installed “MCP Local RAG” server configuration.

  3. Set the BASE_DIR Environment Variable

    • In the configuration panel, find the field for ENV values.
    • Set BASE_DIR to the absolute path of your chosen documents folder (e.g., /Users/yourname/Documents/mydocs).
  4. (Optional) Set Advanced Configuration ENV Values
    You may also set the following optional ENV variables, depending on your needs:

    • DB_PATH: (default is ./lancedb) — Path to your LanceDB storage directory.
    • CACHE_DIR: (default is ./models) — Path to the model cache, if you want the model files stored elsewhere.
    • MODEL_NAME: (default is Xenova/all-MiniLM-L6-v2) — HuggingFace model ID, only change if you want a different Transformers.js-compatible embedding model.
    • MAX_FILE_SIZE, CHUNK_SIZE, CHUNK_OVERLAP: Adjust for performance or special needs. Defaults are usually sufficient.
  5. Save the Configuration
    Click to save/add the ENV values in the FastMCP interface.

  6. Restart the MCP Client

    • For Cursor: Fully quit and relaunch the app.
    • For Codex: Restart the IDE/extension.
    • For Claude Code: No restart needed; changes are picked up immediately.

No API keys or cloud credentials are needed. All data remains local.

You may now begin ingesting, searching, and managing documents using the configured RAG server via your AI client or FastMCP.

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