MCP File Preview Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
The two tools have clearly distinct purposes: analyze_content focuses on structural analysis of HTML content, while preview_file handles file preview and screenshot capture. There is no overlap in functionality, making it easy for an agent to select the appropriate tool without confusion.
Naming Consistency5/5Both tools follow a consistent verb_noun naming pattern (analyze_content and preview_file), with clear, descriptive names that align with their functions. There are no deviations or mixed conventions, ensuring predictability and readability.
Tool Count2/5With only two tools, the server feels thin for a 'File Preview Server' that might be expected to handle more file types or operations beyond HTML. While the tools are focused, the count is borderline too few for the apparent scope, limiting functionality.
Completeness2/5The server is severely incomplete for file preview purposes, as it only supports HTML files with no coverage for other common formats (e.g., images, PDFs, text files). There are significant gaps in the tool surface that will likely cause agent failures when dealing with non-HTML content.
Average 2.9/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 0 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
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.
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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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states what the tool does ('Analyze HTML content structure') without revealing any behavioral traits—such as whether it's read-only, destructive, requires specific permissions, handles errors, or has rate limits. This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with a single phrase, 'Analyze HTML content structure', which efficiently conveys the core purpose without unnecessary words. However, it could be improved by adding a bit more context to enhance clarity without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the analysis returns (e.g., structure details, errors, or metadata), behavioral aspects, or usage context. For a tool with no structured data beyond the input schema, this leaves significant gaps in understanding its full functionality.
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?
The input schema has 100% description coverage, with the parameter 'filePath' clearly documented as 'Path to local HTML file'. The description adds no additional meaning beyond this, as it doesn't elaborate on parameter usage or constraints. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Analyze HTML content structure' states a clear verb ('Analyze') and resource ('HTML content structure'), but it's vague about what 'analyze' entails—does it extract metadata, validate structure, or something else? It doesn't differentiate from the sibling tool 'preview_file', which might also handle HTML files, leaving ambiguity in purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention the sibling tool 'preview_file' or any other context for usage, such as prerequisites or scenarios where this tool is preferred. This leaves the agent without direction on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'preview' and 'capture screenshot' but doesn't specify whether this is a read-only operation, if it modifies files, what permissions are needed, or how the screenshot is returned (e.g., format, storage location). This leaves significant gaps for a tool that interacts with local files and generates outputs.
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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded with the core functionality, making it easy to understand at a glance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of file interaction and screenshot generation, with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns (e.g., screenshot data, file path, error handling), behavioral traits, or integration details, leaving the agent with incomplete information for proper use.
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%, providing clear documentation for all parameters (filePath, height, width). The description adds no additional parameter semantics beyond what the schema already states, so it meets the baseline score of 3 without compensating for any gaps.
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 specific action ('preview' and 'capture screenshot') and resource ('local HTML file'), distinguishing it from the sibling 'analyze_content' which likely performs content analysis rather than visual preview and capture.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, limitations, or comparison with the sibling tool 'analyze_content', leaving the agent without contextual usage instructions.
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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