Generative-UI-MCP
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Only one tool exists, so there is no possible confusion between tools.
Naming Consistency5/5With a single tool, naming is trivially consistent.
Tool Count1/5A server named 'Generative-UI-MCP' should have multiple tools for creating UI components, but only one tool for loading guidelines exists, which is insufficient.
Completeness1/5The server lacks any tools for generating UI widgets, which is its stated purpose. The single tool only loads guidelines, leaving a major gap in functionality.
Average 3.7/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit 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
This repository is licensed under MIT License.
This repository includes a README.md file.
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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 must disclosure behavioral traits. However, it does not explain what happens when guidelines are loaded (e.g., caching, return value, side effects on conversation state). The agent is left unclear about the tool's impact beyond the fact that it loads guidelines.
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 with no wasted words. It front-loads the primary action and includes necessary context and module listing. Every sentence contributes meaning.
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?
For a simple tool with one parameter and no output schema, the description covers when to use and what modules are available. However, it lacks details on what the guidelines contain or how they affect subsequent widget generation, leaving room for ambiguity.
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 the parameter is fully documented in the schema. The description adds no additional meaning beyond listing the available modules, which is already present in the schema. Thus, the description provides no extra value for parameters beyond the schema.
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 that the tool loads design guidelines for generating visual widgets, with a specific verb and resource. It also provides context by recommending to call it before the first widget, making the purpose unambiguous even without siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly instructs to call this tool before generating the first widget, providing clear when-to-use guidance. It does not mention when not to use it, but with no sibling tools, this is sufficient for most cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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- 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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