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Three things MCP can do, and an infinite number of things it can’t do (all of which make it great)
AI agents can interact with the world using tools. Those tools can be generic or specific.
The most general ones, like “run a bash command” and “read and write files” are built into the agent. More specific ones are provided through Model Control Protocol (MCP) servers.
Every tool provided to the agent comes with instructions sent as part of the context. Each MCP server the user configures clogs up the context with instructions and tool definitions, whether the agent needs them for this conversation or not.
If the agent can run a bash command, it can write a curl command or a script to call an API. Why use an MCP server instead?
For remote MCP servers operated by SaaS providers, there are some great reasons.
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