Tools Primitive: Model-Controlled Actions with Side Effects
~15 min read
Tools are executable functions the AI can invoke, usually triggered by the model's own choice — but since they can have real side effects, MCP implementations often require explicit user permission before execution.
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Key points
- •Tools are executable functions the AI can invoke, typically operations with real effects or computation beyond the AI's own capabilities
- •Usually model-controlled: the LLM itself decides when it needs a tool's functionality
- •Registered on the server (e.g. via @mcp.tool()), invoked via tools/call with a name and arguments, returning structured results
- •Since tools can have side effects (file I/O, network calls), MCP implementations often require explicit user permission before execution
- •Analogous to classic function-calling 'functions,' but used in MCP's more flexible, dynamic, discoverable context