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Conference40min
BEGINNER

LLMs, Meet Your Tools: The Magic of Model Context Protocol

Model Context Protocol (MCP) enhances LLM capabilities by integrating external tools, APIs, and data sources within IDEs, fostering intelligent, context-aware workflows. This talk explores MCP's benefits, server integration, and custom capabilities, demonstrating its impact on productivity and automation for developers, DevOps, and ML engineers. MCP is pivotal for modern developer experiences.

Alex Shershebnev
Alex ShershebnevZencoder

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Friday, September 26, 11:20-12:00
Concert Hall
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Model Context Protocol (MCP) is a recent innovation that's quickly gaining traction across the developer ecosystem - and for good reason. It offers a powerful way to extend LLM capabilities by enabling seamless access to external tools, APIs, and data sources directly from within the context of your IDE.
In this talk, we’ll unpack what MCP is, the problems it solves, and why it’s a key enabler for building more intelligent, context-aware workflows. We’ll walk through how to integrate existing MCP servers and how to easily build your own to unlock custom capabilities. You’ll also see real-world examples of chaining multiple MCPs together and connecting them to external systems like Grafana, databases, and internal APIs to supercharge productivity - no window switching required.
Whether you’re a Developer, DevOps, or ML Engineer, MCP opens the door to faster iteration, smarter automation, and context-rich coding experiences. If you care about productivity and developer experience in the age of LLMs, you should care about MCP.
mcp
integration
productivity
workflows
talks.speakers
Alex Shershebnev

Alex Shershebnev

Zencoder

Portugal

Alex Shershebnev is a seasoned Computer Vision and MLOps Engineer with over nine years of experience shaping the future of AI-driven software development. Currently, Alex leads the ML/DevOps team at Zencoder, where he leverages his extensive background in Software Engineering, ML and DevOps to deliver high-quality machine learning solutions. His work spans complex data pipelines, cloud infrastructure management (GCP, Kubernetes), and advanced ML/DevOps pipelines, ensuring scalability and efficiency.

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