An MCP (Model Context Protocol) server is a lightweight program that exposes data, tools, and prompts to an AI application via a standardized open protocol, allowing AI assistants to access external systems, databases, APIs, and files.
MCP servers use JSON-RPC 2.0 for message passing and follow a client-server architecture. Each server exposes three primitives: Resources (readable data or content), Tools (callable functions), and Prompts (reusable templates). A host application (like Claude Desktop or ChatGPT) connects to one or more MCP servers, typically over a stdio transport for local processes or HTTP for remote servers.
The connection begins with a capability-negotiation handshake, then the host can invoke tools, read resources, and use prompts from the server. For example, an MCP server for your filesystem lets an AI assistant read and write files in a designated directory by exposing file operations as tools.
MCP is an open-protocol specification originally released by Anthropic and now developed as an open standard. It integrates naturally with automation workflows and infrastructure tooling, enabling AI assistants to query your infrastructure, parse DNS records, or run diagnostics without building custom integrations.
WarningSecurity: Running third-party MCP servers grants them broad tool and data access with minimal built-in sandboxing. A malicious or buggy server can exfiltrate data or trigger unintended actions. Always vet server code and implement permission prompts before connecting untrusted servers.
InfraNest provides an official MCP server that lets AI assistants query your DNS zones, certificates, uptime status, and more via the same API your integrations use.