We'll first explore how we implemented our MCP server for GraphQL APIs and then use Grafbase extensions to federate non-GraphQL datasources to have them all available for agents without increasing the number of tools.

Problem: Traditional AI application development often involves juggling multiple tools, APIs, and frameworks, leading to inefficiencies, complexity, and limited scalability. Developers are stuck in outdated paradigms that struggle to keep up with the growing demands of modern AI solutions.

Solution: The Model Context Protocol (MCP) offers a transformative approach to AI app development—essentially function calling on steroids. MCP represents a paradigm shift by streamlining the integration and management of core functionalities like file systems, databases, and other essential services through its innovative framework. By enabling seamless connections and robust functionality, MCP revolutionizes how developers build and deploy smarter AI-driven applications.

Description: This hands-on workshop empowers JavaScript developers to explore all facets of MCP development. Participants will learn to build MCP clients, set up MCP servers, and leverage existing MCP servers to create robust AI applications. Through practical exercises, you'll discover how MCP simplifies development, boosts efficiency, and delivers smarter AI-powered solutions. You'll also gain insight into how MCP's groundbreaking function-calling model enhances workflows, allowing seamless management of tasks such as file systems, databases, and more.

Key Takeaways: - Master the fundamentals of MCP and its innovative function-calling approach. - Build and configure MCP clients and servers from scratch. - Explore how to utilize existing MCP servers to streamline development tasks. - Gain hands-on experience in transforming traditional AI workflows into scalable, efficient models.

A new standard is here too make it easier to share resources cross boundaries and bring about the agentic era.