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securityA
license-
qualityA Python-based server that implements the Model Context Protocol to interface with Claude Desktop as an MCP client, supporting interaction through efficient memory management.
Last updated -
1
MIT License
Provides persistent Jupyter kernel execution with tools for running Python code, creating and managing Jupyter notebooks, and maintaining state across multiple executions
Enables persistent 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
📦 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
.venvif 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
.venvin your project directoryInstalls required packages on first notebook creation
Manages kernel lifecycle automatically
📋 Requirements
Python 3.8+
Claude Code CLI (
claudecommand)
🐛 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!"
This server cannot be installed
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