Imagine this: you just need to say to AI:

"Help me organize this month's project materials"

It can automatically analyze your Eagle material library, plan organization steps, and actually execute the operations. This is the experience of AI Agent + Eagle MCP.

What does it mean for AI Agent to "take action"?

Traditional AI can only "answer questions",
but now we have AI Agent: it not only understands your natural language, but can also call tools and actually complete tasks.

The key behind AI Agent is an open standard called Model Context Protocol (MCP), which creates a universal bridge between AI and applications, allowing AI to read and write data and execute processes. Wikipedia

How does Eagle enable AI to truly organize material libraries?

Eagle 5.0 provides an MCP interface, allowing AI Agents (such as ChatGPT, Claude, and other MCP-compatible models) to:

Filter materials by conditions
Automatically categorize and tag
Find duplicate materials and keep the best version
Generate material analysis reports

All these operations can be executed with simple natural language commands, no programming or command learning required.

What does this mean for you?

Using natural language, you can:

Organize messy tags
Filter key files in your material library
Analyze design trends and material usage

AI is no longer just a "chatbot" - it can truly become your Eagle assistant.

Want to enable it right away?

If you want to actually connect AI Agent to Eagle for use,
please check out this article:

👉 Eagle MCP Server Configuration Guide
https://cn.eagle.cool/support/article/eagle-mcp-server

This article provides complete MCP configuration and usage instructions, teaching you how to connect and control Eagle with AI Agent.

AI Agents + MCP: Organize Your Eagle Library with Natural Language