You have likely witnessed the hype-cycle around MCP (the Model-Context Protocol) for LLMs. It was heralded as \"the universal interface between LLMs and the world\" but then faded into the background as attention shifted towards AI Agents. Yet, the background of your AI app is exactly where an MCP should be, and in this talk we cover why. We will tour the MCP protocol, the Python reference implementation, and an example agent using an MCP. Expect protocol flow-charts, architecture diagrams, and a real-world demo. You will walk away knowing the core ideas of MCP, how it connects to the broader ecosystem, and how to power your AI agents.
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Event
October Meetup: Build Your Own AI Agent and Model Context Protocol
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💻Join PyData Boston for an AI Agent extravaganza! We'll have author Emma Saroyan showing us how to build AI agents and a walkthrough of how Model Context Protocol works!
We currently have no food sponsor for this event! Reach out if you're able to sponsor!
RSVP is REQUIRED to attend Do not arrive before 6:30pm!
📅 Schedule: 6:30–7:00 — Networking 7:00–7:15 — Introduction 7:15–8:00 — Talk 1: Build Your Own AI Agent 8:00–8:15 — Break 8:15–9:00 — Talk 2: What Happens Inside an MCP Server? 9:00–9:30 — Networking + Wrap-up
📊 Speakers: [Talk 1] Emma Saroyan Build Your Own AI Agent In this session, I'll walk you through how to build a smart, context-aware agent in just 45 minutes. You'll see how OpenAI APIs, LangChain, and Python can work together to create an agent that goes beyond basic chat. With a demo and easy-to-follow steps, you’ll leave with the confidence to start building and customizing your own AI Assistant. We'll cover: Core principles of AI agents and what makes them different from simple chatbots Step-by-step walkthrough of building an agent with LangChain and OpenAI APIs Demo of an AI agent Practical ways to customize agents for your own use cases
[Talk 2] Sebastian Wallkötter What Happens Inside an MCP Server? You have likely witnessed the hype-cycle around MCP (the Model-Context Protocol) for LLMs. It was heralded as "the universal interface between LLMs and the world" but then faded into the background as attention shifted towards AI Agents. Yet, the background of your AI app is exactly where an MCP should be, and in this talk we cover why. We will tour the MCP protocol, the Python reference implementation, and an example agent using an MCP. Expect protocol flow-charts, architecture diagrams, and a real-world demo. You will walk away knowing the core ideas of MCP, how it connects to the broader ecosystem, and how to power your AI agents.
📍Venue provided by Moderna
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Sessions & talks
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In this session, I'll walk you through how to build a smart, context-aware agent in just 45 minutes. You'll see how OpenAI APIs, LangChain, and Python can work together to create an agent that goes beyond basic chat. With a demo and easy-to-follow steps, you’ll leave with the confidence to start building and customizing your own AI Assistant. We'll cover: Core principles of AI agents and what makes them different from simple chatbots Step-by-step walkthrough of building an agent with LangChain and OpenAI APIs Demo of an AI agent Practical ways to customize agents for your own use cases