mcp-grammar-checker
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
With only a single tool, there is no possibility of ambiguity or misselection. The purpose is clearly singular and distinct.
Naming Consistency5/5There is only one tool, so the naming is trivially consistent. The verb-noun pattern ('check_grammar') is clear and follows a predictable convention.
Tool Count3/5A single tool feels thin for a server, though the scope is narrow (grammar checking). It is borderline per the calibration, likely sufficient for its stated purpose but minimal.
Completeness5/5The tool covers grammar, spelling, and style checking, which appears to be the entire domain. There are no obvious missing operations for a grammar-checking service.
Average 3.3/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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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
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only names the check types and the backend; it does not disclose behavior such as whether the query text is transmitted to an external service (LanguageTool), whether there are length limits, how the result body is structured beyond the output schema, or what happens on an unsupported language. For an unannotated tool this is a meaningful gap.
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?
A single declarative sentence, front-loaded with the verb and object, that wastes no words. It names the three issue categories and the backend in a compact way. Properly sized for the tool's simplicity.
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 output schema covers return values and the input schema fully documents parameters, so those are handled. But with no annotations, the description omits usage guidance, external-service disclosure, and any operational limits. Adequate for a simple two-parameter checker, yet with clear gaps around behavioral context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both 'text' and 'language' are already documented in the schema. The description adds the type-of-issues context (grammar, spelling, style) but does not add parameter-specific meaning beyond what the schema provides. Baseline 3 is appropriate given the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('Check'), resource ('text'), and the range of issues covered (grammar, spelling, style), with a named backend ('LanguageTool'). It is clear what the tool does. With no sibling tools to differentiate against, it cannot distinguish itself further, so it stops short of a 5.
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 — the agent uses this tool whenever text needs a language quality check — but it provides no explicit context about when to use it versus alternatives, nor any exclusions or prerequisites. No siblings exist, so the routing burden is low, but the guidance is still only implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
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- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
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