Which integrations are available for this server?

Provides persistent [Jupyter](/mcp/servers/integrations/jupyter) kernel execution with tools for running Python code, creating and managing Jupyter notebooks, and maintaining state across multiple executions Enables persistent [Python](/mcp/servers/integrations/python) code execution with state preservation, variable persistence across sessions, and automatic virtual environment detection

ML Jupyter MCP - UV-Centric Persistent Jupyter Kernel for Claude

Execute Python code with persistent state across Claude conversations using MCP (Model Context Protocol).

✨ Features

🔄 Persistent State - Variables and imports persist across executions
📓 Notebook Support - Create and manage Jupyter notebooks
🐍 Virtual Environment Detection - Automatically uses project's .venv
🚀 Easy Installation - One-line setup with Claude MCP

Related MCP server: Claude Server MCP

📦 Installation

Quick Install (Recommended)

# Install from PyPI pipx install ml-jupyter-mcp # Add to Claude Code claude mcp add jupyter-executor ml-jupyter-mcp

That's it! The MCP server is now available in all your Claude sessions.

Alternative: Install with UV

# Install with UV tool uv tool install ml-jupyter-mcp # Add to Claude Code claude mcp add jupyter-executor "uvx ml-jupyter-mcp"

Alternative: Clone and Install Locally

# Clone the repository git clone https://github.com/mayankketkar/ml-jupyter-mcp.git cd ml-jupyter-mcp # Create virtual environment uv venv .venv source .venv/bin/activate # Install in development mode pip install -e . # Add to Claude Code claude mcp add jupyter-executor "$(pwd)/.venv/bin/python -m ml_jupyter_mcp.server"

🎯 Usage

Once installed, you can use these MCP tools in any Claude conversation:

Execute Python Code

# In Claude, use: mcp__jupyter-executor__execute_code("x = 42; print(f'x = {x}')") # Later in the same conversation: mcp__jupyter-executor__execute_code("print(f'x is still {x}')") # x persists!

Create Jupyter Notebooks

# Add code cells to notebooks mcp__jupyter-executor__add_notebook_cell("analysis.ipynb", "code", "import pandas as pd")

Check Kernel Status

# Check if kernel is running mcp__jupyter-executor__kernel_status()

Shutdown Kernel

# Clean shutdown when done mcp__jupyter-executor__shutdown_kernel()

🛠️ How It Works

Kernel Daemon - Maintains a persistent Jupyter kernel in the background
MCP Server - Provides tools that Claude can invoke
State Persistence - All variables, imports, and definitions persist across tool calls
Auto-detection - Automatically finds and uses your project's .venv if available

📝 Example Workflow

# Start a data analysis session mcp__jupyter-executor__execute_code(""" import pandas as pd import numpy as np import matplotlib.pyplot as plt # Load your data df = pd.read_csv('data.csv') print(f"Loaded {len(df)} rows") """) # Continue analysis in next message mcp__jupyter-executor__execute_code(""" # df is still available! summary = df.describe() print(summary) """) # Create a notebook with your analysis mcp__jupyter-executor__add_notebook_cell("analysis.ipynb", "code", """ # Data Analysis df.groupby('category').mean().plot(kind='bar') plt.title('Average by Category') plt.show() """)

🔧 Configuration

The tool automatically:

Detects and uses .venv in your project directory
Installs required packages on first notebook creation
Manages kernel lifecycle automatically

📋 Requirements

Python 3.8+
Claude Code CLI (claude command)

🐛 Troubleshooting

MCP tools not showing up?

# Check if server is connected claude mcp list # Should show: # jupyter-executor: ... - ✓ Connected

Kernel not starting?

# Remove and re-add the server claude mcp remove jupyter-executor claude mcp add jupyter-executor "uvx ml-jupyter-mcp"

Port 9999 already in use?

The kernel daemon uses port 9999. If it's in use, the tool will handle it automatically.

🤝 Contributing

Contributions welcome! Please feel free to submit a Pull Request.

📄 License

MIT License - feel free to use in your projects!

🙏 Acknowledgments

Built for the Claude Code community to enable persistent Python execution across conversations.

Pro Tip: After installation, try asking Claude: "Use jupyter-executor to calculate fibonacci numbers and keep them in memory for later use!"

ML Jupyter MCP