# MooseCP Image Server

A Model Context Protocol (MCP) server designed to provide LLMs with efficient, token-optimized visual access to image directories and AI generation capabilities. Instead of dumping full-resolution images (which waste tokens and cause context overflow), MooseCP provides a hierarchical workflow: **List $\rightarrow$ Scan $\rightarrow$ Preview $\rightarrow$ Inspect**.

## ⚠️ AI SLOP DISCLAIMER
This entire project was vibe-coded by an AI. It is 100% slop code. Use it at your own risk.

## Tools Overview

### 📁 `list_directory`
Provides a simplified file-browser view of a directory.
*   **Best for**: Getting a sense of the files present and their basic metadata (size, date).
*   **Features**: Pagination and sorting by name, size, or modification date.

### 🖼️ `contact_sheet`
Generates a high-density grid of thumbnails.
*   **Best for**: Quickly scanning hundreds of images to find a specific one or get a general "vibe" of a folder.
*   **Note**: This tool is paginated. You must iterate through pages to see all images in a folder.
*   **Workflow**: Use the indices shown on the contact sheet to call `preview_image`.

### 🔍 `preview_image`
Provides medium-detail previews optimized for the model's token budget.
*   **Best for**: Comparing a few candidates, inspecting specific details, or selecting a "favorite" image.
*   **Efficiency**: Automatically calculates dimensions to fit the model's patch size (e.g., 48px patches for Gemma 4), ensuring maximum detail without wasting tokens on padding.
*   **Workflow**: Pass indices from the `contact_sheet` or a direct file path.

### 📖 `read_png_metadata`
Extracts AI generation parameters from PNG files.
*   **Best for**: Retrieving prompts, seeds, and model hashes from AI-generated images.

### 📸 `read_image`
Returns the full-resolution image.
*   **Best for**: Final confirmation or deep visual analysis where every pixel counts.

### 🎨 `generate_image`
Triggers an image generation on a local Stable Diffusion WebUI Forge instance.
*   **Workflow**: Always call `get_model_info` first to determine the correct prompting style (e.g., tag-based vs. natural language).
*   **Features**: Supports model-specific presets, resolution presets, and standard parameter overrides.
*   **Output**: Returns a Base64 image for AI analysis and a proxy URL for direct embedding in the chat.

### ℹ️ `get_model_info`
Provides the "manual" for available generation models.
*   **Best for**: Learning the prompting style, recommended settings, and available resolution presets for a specific model.
*   **Workflow**: Call without arguments to see the catalog; call with `model_name` for the detailed guide.

### 🌐 `browse_wikipedia`
Allows the model to browse Wikipedia using its API.
*   **Best for**: Quickly retrieving summaries, structural maps (ToC), or specific section content from Wikipedia without dumping the entire page.
*   **Workflow**: Use `mode='summary'` (default) to get an overview and a Table of Contents. Use `mode='section'` with a linear index from the ToC to dive into specific details.
*   **Features**: Returns raw Wikitext to save tokens, handles redirects, and automatically falls back to a search result list if a page is not found.

---

## Installation & Requirements

### Dependencies
This server requires Python 3.10+ and the following packages:
*   `uvicorn`: ASGI server for the SSE transport.
*   `starlette`: Lightweight ASGI framework.
*   `Pillow`: Image processing and thumbnail generation.
*   `requests`: For communicating with the Stable Diffusion API.

```bash
pip install uvicorn starlette Pillow requests
```

### Setup
1.  Clone this repository to your server.
2.  (Optional) Edit `config.py` to adjust the server port, log level, or token budgets if you are using a model other than Gemma 4.
3.  Run the server:
    ```bash
    python main.py
    ```

## Configuration (`config.py`)

You can tune the server's behavior in `config.py`:

### Server & Logging
- **`HOST` / `PORT`**: The network address and port the server binds to.
- **`LOG_LEVEL`**: Logging verbosity (`DEBUG`, `INFO`, `WARNING`, `ERROR`).
- **`LOG_FILE`**: Path to the server log file.
- **`USER_AGENT`**: The User-Agent string used for API requests (e.g., Wikipedia). Use a browser-like string to avoid 403 Forbidden errors.

### Model & Token Tuning
- **`PATCH_SIZE`**: Set this to `(clip.vision.patch_size * n_merge)` for your specific model to ensure token-perfect resizing.
- **`PREVIEW_TOKEN_BUDGET`**: Controls how many tokens the `preview_image` tool aims for (default: 70).
- **`CONTACT_SHEET_COLS` / `ROWS`**: Adjust the grid size to fit within your model's maximum context window.
- **`CONTACT_SHEET_THUMB_SIZE`**: The pixel size of thumbnails in the contact sheet.

### Image & Font Settings
- **`IMAGE_QUALITY`**: Adjust JPEG compression (1-100).
- **`SYSTEM_FONT_NAMES`**: A list of font names Pillow should attempt to find in the system path.
- **`FALLBACK_FONT_PATHS`**: Absolute paths to `.ttf` files used if no system fonts are found.