docs: add logo to README and watermark-crop usage example
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# local-image-mcp
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<p align="center">
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<img src="assets/logo.jpg" alt="local-image-mcp logo" width="256"/>
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</p>
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Minimal Model Context Protocol server for local image inspection.
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`local-image-mcp` exposes two tools for debugging workflows:
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@@ -81,6 +85,34 @@ Response content includes:
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- a text confirmation
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- an `image` item with base64 data and MIME type
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## Usage example
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The following example shows how an AI agent can use `local-image-mcp` together with a Python script to automatically detect and remove a watermark from an image, keeping the subject centred.
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**Prompt given to the agent:**
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> Crop the image in `assets/` to remove the watermark while keeping the drawing centred. Verify the output and overwrite the original.
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**What the agent did:**
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1. Called `list_local_images` on `assets/` to discover `logo.jpg`.
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2. Called `load_local_image` to inspect the file visually.
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3. Analysed pixel data to locate the watermark (a 4-pointed star in the bottom-right corner at roughly `x: 944–991, y: 944–991` on a 1024×1024 image).
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4. Detected the subject bounding box (`x: 153–870, y: 256–808`, centre ≈ 511, 532).
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5. Computed a square crop centred on the subject with the right/bottom edge stopping at `940 px` (just before the watermark):
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```python
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from PIL import Image
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img = Image.open("assets/logo.jpg")
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cx, cy = 511, 532 # subject centre
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half = min(940 - cx, 940 - cy) # 408 px
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box = (cx - half, cy - half, cx + half, cy + half)
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img.crop(box).save("assets/logo.jpg", quality=95)
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```
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6. Called `load_local_image` again to verify the result — watermark gone, subject centred — then overwrote the original and removed the intermediate file.
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## Resources
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Every successfully loaded image is cached for the current server session and published as a resource:
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