An MCP server library providing LLM integration with structured output, tool execution, streaming, and multi-provider support (OpenAI, Anthropic)
The 'calculate' tool has a clear name, adequate description, and properly typed input schema with enum constraint. However, it is a demonstration/example tool with minimal real-world complexity. The schema is well-formed but the tool itself lacks depth: no output schema documentation, no error handling guidance, no discussion of edge cases (division by zero), and no parameter constraints beyond enum. The description is functional but brief (48 chars), leaving room for LLM optimization. The schema includes all required fields with types and descriptions, meeting basic quality thresholds. Overall, this is a competent but minimal implementation, adequate for a tutorial but lacking production rigor.
Performs a simple mathematical calculation
Missing output schema documentation. The tool description does not specify what the response object contains or its structure. LLMs cannot plan downstream operations without knowing output fields.
No error handling guidance for division by zero or invalid operation states. The tool offers no recovery hints if calculation fails, forcing the LLM to guess the next step.
Tool description is 48 characters, below the recommended 50-200 char range for LLM optimization. It is too terse to guide LLM decision-making robustly.
Numeric parameters 'a' and 'b' lack constraints (min/max, precision). An LLM could pass very large numbers, leading to overflow or unexpected behavior.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | C | 67 | 2025-06-18+ | v2 |
| 2026-03-09 | F | 43 | - | v1 |