Code Report: Model Context Protocol (mCP)

Overview

• Model Context Protocol (mCP): The new standard for building APIs, similar to a USB-C port for AI applications, designed by Anthropic.
• Current Trend: Widely adopted by developers and integrated as a standard in the OpenAI agents SDK.
• Significance: mCP is transforming API development by emphasizing resources and tools conceptually similar to REST API's GET and POST requests.

Key Concepts

• Resources: Used to fetch data without side effects, like a database query.
• Tools: Perform actions, similar to a POST request, like writing to a database.
• Server and Client: The mCP architecture involves a server providing resources and tools, and a client, such as Claude Desktop, utilizing these.

Building an mCP Server

1. Setup: Use platforms like Savola, which offers cloud infrastructure with easy-to-use services and predictable pricing.
2. Implementation:
   • Use the mCPServer class from the SDK to create the server.
   • Define resources and tools to provide and leverage data.
   • Employ tools like Zod for schema validation to ensure reliable data handling.
   • Deploy the server using transport layers like standard IO, server-sent events, or HTTP.

Use Cases and Applications

• Automation and Efficiency: Applications such as automated trading, web scraping, and cloud infrastructure management.
• Integration with Existing Systems: Leverage existing data and Restful APIs to enhance application functionality with mCP.
• Real-World Example: Horse Tender app pivoting to AI for matching and setting up dates between horses.

Industry Impact

• Future of Coding: Anthropic anticipates most code will be AI-generated soon, though skepticism exists.
• Caution Advised: Encouragement to use mCP responsibly to prevent potential data mishaps or AI-related issues.

Additional Resources

• Explore Other Tools: Visit the awesome mCP repo for more tools and applications.
• Savola Sponsorship: Provides a financial incentive to explore their platform via a stimulus check offer.

Conclusion

The mCP is at the forefront of changing how developers build APIs and integrate AI, with potential implications for the broader tech industry in terms of job roles and processes. Users are cautioned to approach this technology responsibly while exploring its vast capabilities.