MCP Server

An MCP server is a process that exposes capabilities — tools it can run, resources it can read, prompts it can offer — to an AI client over the Model Context Protocol. The client discovers what the server can do at connection time rather than having it hard-coded. The problem it solves is combinatorial. Before a shared protocol, every assistant needed a bespoke integration with every system: five assistants and twenty internal services is a hundred connectors, each with its own auth, schema and failure modes. MCP turns that into twenty servers any compliant client can use. For a SaaS company the strategic point is distribution. Shipping an MCP server makes your product callable from inside whatever assistant your customers already use, which is a different channel from your UI and your public API — and it is the one where the buyer is an agent choosing between tools rather than a human choosing between tabs. Two practical cautions. A server exposes real capability, so scope its permissions the way you would an API key, not the way you would a docs page. And treat tool descriptions as an interface: the model picks tools by reading them, so a vague description is a bug that shows up as the model never calling you.