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MCP (Model Context Protocol) is the open standard that lets AI assistants use outside tools — databases, browsers, APIs, file systems — through one interface. Setting up an MCP server means your assistant stops being a chat window and starts doing real work against your real systems, which is exactly why setup deserves care.
Name the concrete thing you want your assistant to do (query the production database read-only, manage your calendar, control a browser). That determines which server you need — installing servers speculatively just widens your attack surface.
The MCP ecosystem already covers most common systems. Evaluate an existing server's source and maintenance before writing your own; you write a custom server when your target is internal or the existing one lacks the operations you need.
Each MCP client (Claude Code, Cursor, and others) has a config file where you declare the server: the command to launch it, arguments, and environment. After registering, restart the client and confirm the server's tools appear.
The server runs with the credentials you give it — so give it the minimum: a read-only database user, an API key scoped to one workspace, a directory allowlist for file access. Never hand an MCP server your admin credentials.
Before trusting it in real work, exercise the failure modes on purpose: ask for something out of scope, confirm writes are blocked where you expect, check what gets logged. Five minutes of adversarial testing tells you what a month of normal use won't.
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