Build AI Agents with MCP in Langflow 1.4
Whether you’re orchestrating tasks across agents or powering external apps with your Langflow logic, Projects and MCP give you a powerful new way to modularize and scale your GenAI development.
Want to connect your AI agents to tools, context, and data—without hardcoding everything?
MCP (Model Context Protocol) makes it easier to use tools and data in AI Agents. Let’s deep dive into Langflow 1.4, a major update to MCP functionality, where we’ll show how to expose and configure your project-based flows as MCP-compatible tools. Whether you’re orchestrating tasks across agents or powering external apps with your Langflow logic, Projects and MCP give you a powerful new way to modularize and scale your GenAI development.
If you’re using MCP in Langflow today, you definitely want to upgrade to 1.4. If you’re not, now’s the time to get into MCP.
What you’ll learn:
How Langflow Projects help you organize and scale workflows
How to expose your flows, tools & files via MCP
Use Langflow as an MCP server (and client!) with apps like Claude & Cursor
Live Demo: We’ll play Wordle… entirely over MCP
Speakers
David Jones-Gilardi
Developer Relations Engineer
DataStax
Melissa Herrera
Developer Relations
DataStax