What is a Remote MCP Server?

The Model Context Protocol standardizes how an AI model or agent discovers and invokes external tools — search a database, send a Slack message, query a CRM. MCP servers can run locally, spawned as a subprocess on the same machine as the agent, or remotely, hosted as a service the agent connects to over the network using HTTP with server-sent events for streaming responses. Remote servers shift the operational burden — hosting, scaling, credential storage, uptime — onto the server operator instead of every client machine. This matters most for tools that require centrally managed state or credentials: a remote MCP server can hold a shared OAuth connection to a third-party API and broker access for many agent sessions, rather than requiring each local install to separately manage its own token store. It also enables multi-tenant scenarios where one hosted MCP server serves many different users or organizations, each scoped correctly by an authenticated session rather than by what happens to be installed on a laptop. The tradeoff is a network dependency and a new trust boundary — a remote MCP server is effectively a third party the agent grants tool access to, which makes authentication, rate limiting, and request validation between the agent and the server a real security surface.