Explore the fundamentals of Model Context Protocol (MCP) with this open-source curriculum. It provides practical, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust, and Python, empowering developers to create modular and secure AI workflows.
claude install microsoft/mcp-for-beginnersExplore the fundamentals of Model Context Protocol (MCP) with this open-source curriculum. It provides practical, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust, and Python, empowering developers to create modular and secure AI workflows.
Build modular AI applications that can be easily maintained and updated.
Create secure AI services that protect sensitive data and ensure compliance.
Orchestrate AI workflows that integrate multiple services and languages.
Implement cross-language solutions that allow seamless interaction between different programming environments.
claude install microsoft/mcp-for-beginnersgit clone https://github.com/microsoft/mcp-for-beginnersCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
I want to learn about the Model Context Protocol (MCP) for [COMPANY] in the [INDUSTRY] industry. Can you provide a brief overview of its fundamentals and practical applications, including examples in [LANGUAGE]?
### Overview of Model Context Protocol (MCP)
The Model Context Protocol (MCP) is a framework designed to enhance the modularity and security of AI workflows. It allows developers to create reusable components that can communicate effectively across different programming languages.
### Practical Applications
- **Cross-Language Compatibility**: MCP supports .NET, Java, TypeScript, JavaScript, Rust, and Python, making it versatile for various development environments.
- **Modular Design**: By using MCP, developers can break down complex AI systems into manageable modules, improving maintainability.
### Example Usage in Python
```python
# Example of a simple MCP implementation in Python
class ModelContext:
def __init__(self, model_name):
self.model_name = model_name
def run(self, data):
# Process data with the specified model
return f'Processed {data} with {self.model_name}'
context = ModelContext('MyModel')
result = context.run('sample data')
print(result) # Output: Processed sample data with MyModel
```Unlock data insights with interactive dashboards and collaborative analytics capabilities.
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