mcp-calculator
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Only one tool exists, so there is no possibility of confusion or overlap between tools.
Naming Consistency5/5With a single tool named 'calculate' using a simple verb format, naming is trivially consistent.
Tool Count3/5One tool is at the low end of typical scope; while a calculator can be a single function, it might benefit from separating domains (e.g., arithmetic, algebra) for clarity.
Completeness4/5The tool claims to support a wide range of mathematical operations (arithmetic, algebra, trigonometry, etc.), covering most common computation needs, though a dedicated tool for statistics or units could be argued.
Average 3.9/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It mentions the library (MathJS) and supported capabilities, but does not specify whether the operation is read-only, error behavior, or side effects. For a calculation tool, it is likely safe, but the description could be more transparent about return values and error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loads the core purpose, and includes a concise list of supported features without unnecessary elaboration. Every sentence is informative and contributes to understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter, but it lacks an output schema. The description does not mention the return format or potential errors. For a calculation tool, completeness could be improved by noting the result type or error handling, so a score of 3 is appropriate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, providing baseline 3. The description adds value by explaining that the expression is evaluated using MathJS and listing supported mathematical domains, which enriches the parameter meaning beyond the schema's examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool evaluates mathematical expressions using MathJS, with a specific verb ('Evaluate') and resource ('mathematical expression'). It lists supported areas (arithmetic, algebra, trigonometry, etc.) and distinguishes itself from potential siblings by mentioning MathJS's full capabilities, which is helpful even in the absence of sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for any mathematical expression evaluation but does not explicitly state when to use this tool vs alternatives, nor does it mention when not to use it. Since there are no sibling tools, this is a minor gap, but the lack of explicit guidance results in a score of 3.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
Glama performs regular codebase and documentation scans to:
- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
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