This MCP server exposes 2 tools with basic Spring-AI annotations. Both tools have descriptions and are READ_ONLY, but critically lack comprehensive schema documentation and parameter descriptions. The naming is reasonable (verb_noun pattern: getEmployee, getAllEmployee), but parameter guidance is sparse. The server appears functional but falls well below production quality standards for agentic tool patterns.

• Rename getAllEmployee to list_employees (snake_case, explicit list_ prefix). Helps LLMs recognize it as a discovery/enumeration tool.
• Add detailed description to getEmployee's 'name' parameter: 'Employee full name (case-insensitive, e.g. "Hassan" or "Mohamed"). If unknown, call list_employees first.'
• Document the Employee output schema explicitly. Specify fields: name (string), salary (integer, in USD), years (integer, tenure in years). State which fields are guaranteed to be present.
• Add pagination to getAllEmployee: include offset (default 0) and limit (default 20, max 100) parameters. Return total_count and next_offset in response. Update description: 'List all employees (paginated, default 20 per page).'
• Add error handling guidance: 'If employee not found, return a 404 with message: "Employee \"<name>\" not found. Call list_employees to see available employees."'
• Consider idempotency hint: Both tools are READ_ONLY and safe to retry. Add a toolAnnotation or note: '@McpTool(readOnlyHint = true)' to signal this to agents.
• Add examples to descriptions (in text, not parameter values): 'Get information about a given employee (e.g., to retrieve Hassan's salary and tenure)' makes intent clearer.