🤖 CLAUDE DESKTOP SETUP GUIDE
STEP 1: PREPARE WORKSPACE
Claude is sandboxed. It cannot see your Desktop. You must create a bridge.
1. Create this EXACT folder on your PC: C:\\Claude_Work
2. Move your hieroglyph images INSIDE this folder.
STEP 2: VERIFY PYTHON
The code below assumes Python is at: C:\\Python313\\python.exe
Check your path: Open CMD and type where python.
Note: If your path is different, replace the path in the JSON code block below before copying.
STEP 3: CONFIGURE CLAUDE
1. Open Config: %APPDATA%\\Claude\\claude_desktop_config.json
2. Paste the JSON below into the "mcpServers" section.
3. IMPORTANT: Close Claude from the System Tray (near the clock) and restart it.
STEP 4: USAGE
Prompt Claude: "Analyze the image at C:\\Claude_Work\\my_tablet.jpg"
"""
claude_json_content = """{
"mcpServers": {
"gradio": {
"command": "npx",
"args": [
"mcp-remote",
"https://youkii-xr-hieroglyph-mcp-server.hf.space/gradio_api/mcp/",
"--transport",
"streamable-http"
]
},
"upload_helper": {
"command": "C:\\\\Python313\\\\python.exe",
"args": [
"-m",
"gradio",
"upload-mcp",
"https://youkii-xr-hieroglyph-mcp-server.hf.space/",
"C:\\\\Claude_Work"
]
}
}
}"""
# --- 4. MAIN APP ASSEMBLY ---
# JS: Toggle Theme AND Add Mouse Trail
js_code = """
() => {
// 1. Toggle Logic
const toggleTheme = () => {
document.body.classList.toggle('light-mode');
const container = document.querySelector('.gradio-container');
if (container) container.classList.toggle('light-mode');
}
// 2. Mouse Trail Logic
const addTrail = () => {
document.addEventListener('mousemove', function(e) {
// Rate limit to prevent too many elements
if (Math.random() > 0.5) return;
const dust = document.createElement('div');
dust.classList.add('gold-dust');
dust.style.left = e.clientX + 'px';
dust.style.top = e.clientY + 'px';
document.body.appendChild(dust);
// Remove after animation
setTimeout(() => {
dust.remove();
}, 600);
});
}
// Initialize
addTrail();
// Return the toggle function for the button click
return toggleTheme;
}
"""
# We need to run the trail logic on load, but Gradio JS usually runs on events.
# We will attach the trail logic to the body load via an HTML script injection.
trail_script = """
"""
with gr.Blocks(title="Rosetta Decoder") as demo:
# Inject CSS & Trail Script
gr.HTML(f"")
gr.HTML(trail_script)
# Top Section
with gr.Row(elem_classes="header-row"):
with gr.Column(scale=4):
gr.HTML(header_html)
with gr.Column(scale=1):
# JS-based Toggle
btn_toggle = gr.Button("🌗 Day / Night", elem_classes="toggle-btn")
gr.HTML(mission_html)
# Workspace
with gr.Row():
with gr.Column(scale=1):
gr.HTML('
INPUT IMAGE
')
with gr.Tabs():
with gr.TabItem("📜 Upload File"):
img_upload = gr.Image(type="pil", sources=["upload", "clipboard"], label="Upload", height=320)
slider_upload = gr.Slider(0.1, 1.0, 0.25, label="Scan Sensitivity")
btn_upload = gr.Button("🔍 START DECODING", elem_classes="primary-btn")
with gr.TabItem("🎥 Live Camera"):
img_cam = gr.Image(type="pil", sources=["webcam"], label="Camera", height=320)
slider_cam = gr.Slider(0.1, 1.0, 0.25, label="Scan Sensitivity")
btn_cam = gr.Button("🔍 LIVE DECODE", elem_classes="primary-btn")
gr.HTML('
')
with gr.Column(scale=1):
gr.HTML('
AI ANALYSIS RESULTS
')
out_image = gr.Image(label="Decoded Result", interactive=False)
btn_download = gr.DownloadButton("💾 DOWNLOAD RESULT", visible=True)
out_report = gr.Textbox(label="Analysis Log", lines=6, elem_classes="report-box", placeholder="Waiting for data stream...")
with gr.Accordion("Raw Glyph Data (JSON)", open=False):
out_json = gr.JSON(label="JSON Data")
gr.HTML('
')
# Footer
gr.HTML(guide_instructions_html)
gr.Code(value=claude_json_content, language="json", label="claude_desktop_config.json", interactive=False, lines=15)
gr.HTML("
")
# Wiring
# The toggle button triggers a JS function that adds the 'light-mode' class
btn_toggle.click(None, None, None, js="() => { document.body.classList.toggle('light-mode'); document.querySelector('.gradio-container').classList.toggle('light-mode'); }")
btn_upload.click(fn=detect_hieroglyphs, inputs=[img_upload, slider_upload], outputs=[out_image, out_json, out_report, btn_download])
btn_cam.click(fn=detect_hieroglyphs, inputs=[img_cam, slider_cam], outputs=[out_image, out_json, out_report, btn_download])
if __name__ == "__main__":
demo.launch(mcp_server=True, ssr_mode=False, allowed_paths=["/tmp"])