Arguments
Arguments (π solution)
π¨βπΌ Well done! You've just made your MCP tool dynamicβnow it can accept arguments
from the client and return results based on user input. This is a huge step
toward building truly interactive and useful AI-powered systems.
What's cool about this is the end user can use natural language to describe the
arguments they want to pass to the tool. For example, they could say "add one
and two" and the tool would automatically parse that into the
firstNumber and
secondNumber arguments. They could even do it in another language!Watch this for more on the idea of overcoming language barriers:
Accessibility in AI: How MCP Makes Language Barriers Disappear
AI and Mcp Language Barriers Dbjmj
Taking it further, the LLM could derive those arguments from the conversation
which could include context from other tools. Tools working together to solve a
complex problem!
By using Zod for input validation, you've ensured your tool
is robust and safe, and you now have a pattern for building more complex tools
in the future.
Key learnings from this step:
- How to define and validate tool arguments using Zod
- How to access arguments in your tool handler
- How to return dynamic results based on user input
You're now ready to build all sorts of powerful, parameterized tools!
