Developing With Streamlit
Develop interactive data apps quickly using Streamlit’s intuitive tools – boosting your prototyping and deployment workflow.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add developing-with-streamlit npx -- -y @trustedskills/developing-with-streamlit
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"developing-with-streamlit": {
"command": "npx",
"args": [
"-y",
"@trustedskills/developing-with-streamlit"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The developing-with-streamlit skill enables AI agents to create and manage interactive data applications using Streamlit, a Python framework for building web apps. It supports real-time data visualization, user input handling, and deployment of dashboards with minimal code.
When to use it
- Building a dashboard to visualize sales data in real time
- Creating an interactive tool for users to filter and explore datasets
- Developing a prototype for a machine learning model's output visualization
Key capabilities
- Real-time data rendering
- Support for widgets like sliders, buttons, and text inputs
- Integration with Python libraries such as Pandas and Matplotlib
- Easy deployment of apps using Streamlit Cloud or local servers
Example prompts
- "Create a Streamlit app that displays a line chart of stock prices over time."
- "Build an interactive dashboard where users can select a region and see corresponding sales data."
- "Generate a Streamlit application to visualize the results of a machine learning model."
Tips & gotchas
- Ensure Python and Streamlit are installed before using this skill.
- Some advanced features may require additional libraries or configurations.
Tags
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
🏢 Official
Published by the company or team that built the technology.