MCP Servers
- What is an MCP server?
An MCP server is a program that exposes tools, data, or services to AI models using the Model Context Protocol (MCP), an open standard created by Anthropic. It acts as a bridge between an LLM and external systems. - How does an MCP server work?
An MCP server runs as a separate process, communicates with an MCP host over a transport like stdio or HTTP, and exposes tools, resources, and prompts. The host's LLM decides when to call them, and the server executes the request and returns results. - Why use MCP instead of direct API calls?
MCP provides a standardized, reusable interface that works across multiple AI hosts, reducing custom integration code. Direct API calls are simpler for one-off use cases but don't scale across models or applications. - Can I build my own MCP server?
Yes, you can build your own MCP server using official SDKs in Python, TypeScript, or other languages. The protocol is open and designed to be implementable by individual developers. - Is MCP server secure?
MCP servers can be secure, but it depends on implementation. They introduce risks like prompt injection and unauthorized access, so you must follow security best practices. - How do I connect an AI assistant to an MCP server?
You connect an AI assistant to an MCP server by configuring the assistant to use the MCP client, which communicates with the server via a defined protocol (often over stdio or HTTP).