# MCP Translator Server

This project provides an MCP (Model Context Protocol) server designed to facilitate the translation of long-form text documents.

## Features

*   Accepts paths to multiple text files for concurrent translation jobs.
*   Splits each text file into manageable chunks.
*   Stores chunks and their translation status in a SQLite database (`translation_progress.db`), keeping track of which file each chunk belongs to.
*   Provides tools to:
    *   Initialize or restart the translation process for a specific file (`start_translation file_path=...`). Clears previous progress for that file if it existed.
    *   List all ongoing translation jobs and their progress (`list_jobs`).
    *   Fetch the next untranslated chunk for a specific file (`get_next_chunk file_path=...`).
    *   Submit the translation for a specific chunk ID (`submit_translation chunk_id=... translated_text=...`).

## Setup

1.  Install dependencies:
    ```bash
    pip install .
    # Or pip install -e . for development mode
    ```

2.  Download the spaCy model:
    ```bash
    python -m spacy download xx_sent_ud_sm
    ```

## Running the Server

```bash
mcp-translator
```

This will start the MCP server, listening for client connections. The database file (`translation_progress.db`) will be created in the same directory as `server.py`.

## Usage

Connect an MCP client (like a compatible AI assistant or script) to the running server. The client can then use the available tools, making sure to specify the `file_path` where required (`start_translation`, `get_next_chunk`), to manage the translation workflow for different files. 