The Demo server defines a single tool 'add' with minimal quality. The tool name lacks a verb prefix (should be 'add_numbers'), the description is extremely terse (11 chars, below baseline 34 chars), and parameter descriptions are completely missing (both 'a' and 'b' have null descriptions). The input schema is present but undocumented. No output schema is documented. No error handling, recovery guidance, or composition patterns are evident. The server also exposes a resource and prompt, but evaluation focuses on the tool definition quality.

• Rename 'add' to 'add_numbers' to follow verb_noun convention and help LLMs parse intent from the tool name alone.
• Expand the description from 'Add two numbers' to a 50-150 character description that explains WHAT it does, WHEN to use it (e.g., 'Use when the LLM needs to perform arithmetic addition'), and WHAT it returns (e.g., 'Returns the sum as an integer'). Example: 'Add two integers together and return the sum. Use this when you need to perform arithmetic addition on numeric values.'
• Add descriptions to both parameters: 'a': 'The first integer operand', 'b': 'The second integer operand'.
• Document the output schema explicitly. Add a structured return statement with type hints visible to the MCP introspection layer, or add a docstring describing the return type as 'Returns: integer (the sum of a and b)'.
• Implement input validation and error handling. Catch edge cases (e.g., None values, type mismatches) and return structured error messages: 'Invalid input: both a and b must be integers. Got a={a} (type={type(a).__name__}), b={b} (type={type(b).__name__}).'
• Consider whether this is a useful production tool. A simple addition function is likely a demo/toy. For real MCP servers, prioritize tools that integrate with external APIs, databases, or services where agents cannot natively access them.