Jupyter MCP服务器

graph TD
    A[AI Agent/Claude] --> B[MCP Server]
    B --> C[Jupyter Server API]
    B --> D[WebSocket Channels]
    C --> E[Kernel Management]
    D --> F[Real-time Execution]
    F --> G[Output Capture]
    G --> H[Image Extraction]
    G --> I[Text Processing]
    B --> J[Notebook Files]

# 1. Create and execute visualization code
add_execute_code_cell(cell_content="""
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns

# Generate sample data
data = np.random.normal(0, 1, 1000)

# Create beautiful visualization
plt.figure(figsize=(12, 8))
plt.subplot(2, 2, 1)
plt.hist(data, bins=50, alpha=0.7, color='skyblue')
plt.title('Distribution Analysis')

plt.subplot(2, 2, 2)
sns.boxplot(y=data)
plt.title('Box Plot Analysis')

plt.tight_layout()
plt.show()
""")

# 2. Extract the generated image
get_cell_image_output(cell_index=0)

# 3D surface visualization
add_execute_code_cell(cell_content="""
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
import matplotlib.pyplot as plt

fig = plt.figure(figsize=(12, 9))
ax = fig.add_subplot(111, projection='3d')

# Create mesh
x = np.linspace(-5, 5, 100)
y = np.linspace(-5, 5, 100)
X, Y = np.meshgrid(x, y)
Z = np.sin(np.sqrt(X**2 + Y**2))

# Render surface
surface = ax.plot_surface(X, Y, Z, cmap='plasma', alpha=0.9)
ax.set_title('3D Mathematical Function')
plt.colorbar(surface)
plt.show()
""")

# Extract 3D visualization
get_cell_image_output(cell_index=1)

# Test image extraction capabilities
python tests/test_image_extraction.py

# Test notebook operations  
python tests/test_notebook_save.py

jupyter-mcp-server/
├── src/
│   └── jupyter_mcp_server.py      # Main MCP server implementation
├── notebooks/                     # 📓 All Jupyter notebooks are created here
│   └── mcp_notebook.ipynb         # Default notebook for MCP operations
├── tests/
│   ├── test_image_extraction.py   # Image extraction tests
│   └── test_notebook_save.py      # Notebook operation tests
├── scripts/
│   ├── start_jupyter.sh           # Jupyter server startup script
│   └── get_claude_config.py       # Claude configuration generator
├── examples/
│   ├── claude_desktop_config.json # Example configuration
│   ├── mcp_notebook.ipynb         # Example notebook
│   └── new_notebook.ipynb         # Sample notebook
├── docs/
│   ├── MCP_TOOLS_SUMMARY.md       # Complete tool reference
│   ├── SETUP.md                   # Setup guide
│   └── IMAGE_EXTRACTION_README.md # Image extraction guide
├── requirements.txt               # Python dependencies
├── pyproject.toml                 # Project configuration
└── README.md                      # Project documentation