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Creating Custom AI Agents
Creating Custom AI Agents
Introduction to Model Context Protocol
The model context protocol (MCP) is a system that helps AI connect to different software and services in an organized and secure way. Its main purpose is to give AI access to the right information, with the right context, so it can provide more helpful and reliable answers or actions.
Model Context Protocol (MCP) simplifies building AI agents by managing context and data flow between models and external tools using a unified structure. Instead of creating everything from scratch, you just set what you want the agent to do, what information it needs, and what services it should use, making the whole process simpler and more reliable.
- The MCP server works as a connector. It talks to local data on your computer or online services, handling requests and sending back the right information.
- Clients are programs or tools like Claude or IDEs that send requests to the MCP server asking for data or actions.
- Context adds useful details to each request, like what task you want to do or what data is involved, so the system can handle it properly.
On your computer, the MCP client (like Claude or another tool) sends a request via the MCP protocol to an MCP server. The server pulls data from a local source (file, database) or an online service, then sends the info back to the client, so your tool can use it.
This setup acts as a smart middle layer, letting your AI or tools connect to many sources easily, without you manually managing each connection.
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