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Templates

MINEO's Templates feature allows users to instantly generate new projects with a pre-configured structure and setup, directly from the file explorer. This accelerates development by providing ready-to-use, boilerplates.

How to Import from a Template​

To generate a new project from a template:

  1. Navigate to the file explorer within your project.
  2. Select the option Import from template.
  3. In the dialog, you will see the list of available templates. Select the one that fits your needs.
  4. In the Name field, enter a name for the new Live App. It defaults to the template's name. MINEO checks availability as you type and flags it as available or already in use (a name is taken when a folder with that name already exists at the target location, or a Live App in the project already uses it).
  5. Click Import. The template's structure is cloned into a folder with that name at your current location in the file explorer, and the Live App is created with the same name. You may later rename or move the folder within your project.

Available Templates​

Streamlit Template​

This template provides a complete foundation for building and deploying Streamlit applications on MINEO.

Repository URL: https://github.com/MINEO-app/Streamlit-Project-Template

What's included:

  • Pre-configured Environment: A requirements.txt file with essential libraries (streamlit, pandas, numpy, etc.).
  • Project Structure: A logical folder structure separating application logic, assets, and utility modules.
  • Sample Application: A basic, runnable Streamlit app (app.py) demonstrating layout, interactivity, and data display.
  • Deployment Ready: Configuration and setup optimized for one-click execution within the MINEO platform.
  • Best Practices: Code organization following common patterns for maintainable Streamlit projects.

How to use it:

  1. Select the Streamlit Template from the template list.
  2. In the Name field, enter a name (e.g., my_streamlit_app).
  3. Click Import. A new folder will appear with the full template structure.
  4. Navigate into the new directory. The Live App (Streamlit Live App) is ready to be executed. More info about Live Apps
  5. You can immediately run the application within MINEO to see the sample in action, or start editing the files to build your own logic.

MCP Template​

A FastMCP server template, ready for use within MINEO Assistants or in other deployments.

Repository URL: https://github.com/MINEO-app/FastMCP-Project-Template

What's included:

  • Ready-to-run FastMCP server: An app.py you can deploy as a Live App to expose tools over MCP.
  • Pre-configured entrypoint: MINEO runs it with pip install --no-cache-dir fastmcp && python app.py (the FastMCP entrypoint preset).
  • Assistant-ready: A starting point for tools you can connect to a MINEO Assistant through Integrations → MCP, or to any external MCP client.

How to use it:

  1. Select the MCP Template from the template list.
  2. In the Name field, enter a name (e.g., my_mcp_server).
  3. Click Import. A new folder will appear with the template structure.
  4. Deploy it as a Live App using the FastMCP entrypoint. For an MCP server scoped per user, see Per-user authenticated MCP.
  5. Connect the running server to an Assistant from Integrations → MCP to make its tools available in Threads.
Deploy it as an MCP server

This template is meant to run as a Live App. Start with Live Apps to deploy it, and to expose its tools securely with per-user identity, follow Per-user authenticated MCP. Then add the deployed URL under the Assistant's Integrations → MCP section.

Benefits of Using Templates​

  • Rapid Setup: Skip manual configuration of dependencies, and project structure.
  • Consistency: Ensures all projects follow the same organizational standards and best practices.
  • Focus on Logic: Start coding your application's unique features immediately, not the boilerplate.
  • Platform Optimized: Templates are specifically configured to leverage MINEO's execution and deployment capabilities seamlessly.

Note: More templates for other frameworks and use cases (like FastAPI, Data Pipelines, Machine Learning) will be added in the future. This feature allows teams to standardize and share project starters across an organization.