MCP server

An MCP server is a small service that exposes tools, data or actions to an AI model through the Model Context Protocol, the open standard Anthropic introduced for connecting models to the outside world. Instead of an AI being trapped with only what is in its prompt, an MCP server lets it query your database, read your project tracker, hit an API or run a defined action, all through one consistent interface.

Think of it as a universal adapter between your AI and your tools. Rather than building bespoke integrations for every model and every service, you write one MCP server and any compatible AI can use it.

Here is what that looks like in practice. Say you're running your engineering work in Linear: an MCP server lets an agent read your open issues, comment on them and move tickets across the board without you ever leaving the chat. Say your product data lives in Supabase: a Supabase MCP server lets the agent run real queries against your tables, so it answers "how many trials converted last week" from live rows instead of guessing. Or say you track hours in Toggl: a small MCP server can start timers and pull a weekly summary on command.

For a founder building an agentic workflow, this is how you give an agent real capability. The discipline is to stay lean, every connected server is a permanent cost on the model's attention and a possible security surface, so wire only what earns its place.