Get started with CData Connect AI for free today to build your AI agent: https://bit.ly/4dsrmLL

Building an AI agent seems pretty simple on paper. But as soon as you try to deploy it, use it on a real world scenario or hand it off to someone like a client - it becomes a lot more difficult. When you actually use an AI agent in the real world, you need three things: connectivity, context, and control. I'm going to show you how to fix that problem.

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⏳ Timestamps ⏳
00:00 | Overview
01:22 | CData ConnectAI
02:32 | Setup/Getting Started
06:48 | Connecting Data Sources
08:42 | Interacting with Data
10:21 | Connecting to Claude
12:33 | Access Controls
14:00 | Data Specific Views
15:39 | Connecting to Langchain

Hashtags
#CData #AIAgents #SoftwareEngineer

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A sponsored tutorial demonstrating how to build a production-ready AI agent using CData's Connect AI platform. The platform acts as a unified data layer connecting multiple sources (MongoDB, QuickBooks, etc.) to LLMs via a single MCP server. Key benefits covered include simplified multi-source connectivity, reduced token costs by offloading data processing, and centralized role-based access control. The tutorial walks through connecting data sources, integrating with Claude via the built-in connector, and programmatically connecting via LangChain in Python using MCP adapters.

How to Build an AI Agent That Interacts With All Your Data Sources