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User Guide

Learn how to effectively use napari MCP server with AI assistants for microscopy analysis and image processing workflows.

Available Guides

Guide Description Status
🔌 napari Plugin Use napari-mcp as a plugin for direct session integration ✅ Available
🎮 Basic Usage Get started with fundamental operations and common tasks Coming soon
🚀 Advanced Workflows Complex analysis pipelines and automation techniques Coming soon
🛡️ Security Important security considerations and best practices Coming soon
🔧 Troubleshooting Solutions to common issues and debugging tips ✅ Available
  • napari Plugin Guide - Use as a napari plugin for direct integration (available now)
  • Troubleshooting Guide - Solutions to common problems (available now)
  • Python Integration - Custom integrations with OpenAI, Anthropic, etc. (available now)
  • Basic Usage Guide - Coming soon
  • Advanced Workflows - Coming soon
  • Security Guide - Coming soon

What You'll Learn

Basic Usage Guide

  • Loading and displaying images in napari
  • Creating and managing different layer types
  • Basic viewer navigation and controls
  • Taking screenshots and exporting data

Advanced Workflows

  • Multi-dimensional data handling (3D, 4D, time series)
  • Custom analysis with code execution
  • Package installation and environment management
  • Automated processing pipelines with Python scripts (see examples)

Security Considerations

  • Understanding code execution risks
  • Safe practices for AI-assisted analysis
  • Network security and access control
  • Production deployment guidelines

Troubleshooting

  • Common setup and configuration issues
  • Platform-specific problems
  • Performance optimization tips
  • Debugging techniques

Getting the Most from This Guide

Recommended Learning Path

  1. Start with Basic Usage - Get comfortable with fundamental operations
  2. Try Security practices - Understand the implications of code execution
  3. Explore Advanced features - When you're ready for complex workflows
  4. Keep Troubleshooting handy - For when things don't go as expected

Prerequisites

Before diving into these guides, ensure you have:

  • ✅ Working napari MCP server - Follow our Getting Started guides
  • ✅ AI assistant connected - Claude Desktop, Cursor, etc. properly configured
  • ✅ Basic familiarity - Understanding of images and microscopy concepts

Example Workflows by Discipline

  • Cell imaging - Load fluorescence images, adjust contrast, measure features
  • Time-lapse analysis - Navigate temporal data, track objects over time
  • 3D reconstruction - Visualize Z-stacks, create volume renderings
  • Multi-channel analysis - Overlay channels, analyze co-localization
  • Surface analysis - Load SEM/AFM data, measure surface features
  • Crystal structure - Analyze diffraction patterns, identify phases
  • Defect analysis - Identify and quantify material defects
  • Multi-scale imaging - Connect nano to macro scale observations
  • Histology - Analyze tissue sections, quantify staining patterns
  • Developmental biology - Track embryonic development over time
  • Neuroscience - Analyze neural networks, trace connections
  • Plant biology - Study cellular structures, analyze growth patterns
  • Computer vision - Develop and test image processing algorithms
  • Machine learning - Prepare training data, validate model outputs
  • Automated analysis - Create reproducible processing pipelines (Python examples)
  • Interactive exploration - Use AI to guide data discovery

Community and Support

  • GitHub Issues - Report bugs and request features
  • Discussions - Share workflows and ask questions
  • Documentation - Contribute improvements and examples
  • Examples Repository - Share analysis scripts and notebooks

Ready to become a napari MCP expert? Choose your starting point above and let's dive in! 🔬✨