MCP Markdown Conversion Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
With only one tool, there is no possibility of confusion or overlap between tools. The single tool 'to-markdown' has a clearly defined and distinct purpose: converting various file formats to markdown descriptions.
Naming Consistency5/5Since there is only one tool, naming consistency is inherently perfect. The tool name 'to-markdown' follows a clear verb-object pattern that is appropriate for its function.
Tool Count2/5A single tool is too few for a server with a broad scope like 'Markdown Conversion Server' that handles multiple file types. This thin surface may force agents to rely on this one tool for all conversion tasks, lacking specialized operations for different formats or scenarios.
Completeness2/5The tool set is severely incomplete for the server's purpose. While 'to-markdown' covers conversion, there are obvious gaps such as no tools for validating markdown, handling conversion errors, or providing metadata about supported formats, which limits agent workflows.
Average 2.9/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 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 is passing
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 carries full burden. It mentions what the tool does but lacks behavioral details like whether it processes files locally or remotely, error handling for unsupported formats, performance characteristics, or output format specifics. The description is functional but minimal.
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 front-loads the core purpose and lists supported file types without unnecessary elaboration. Every word contributes to understanding the tool's scope, making it appropriately concise.
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 no annotations and no output schema, the description is incomplete. It doesn't explain what the generated markdown includes, how errors are handled, or any behavioral traits. For a tool with one parameter but significant implicit complexity (file processing), more context is needed.
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 schema already documents the 'filePaths' parameter. The description adds no additional parameter semantics beyond implying file type support, which is partially covered by the schema's lack of constraints. Baseline 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.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate markdown description for files' and lists specific file types it supports. It uses a specific verb ('Generate') and identifies the resource ('files'), but since there are no sibling tools, it doesn't need to differentiate from alternatives.
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?
The description provides no guidance on when to use this tool versus alternatives or any contextual prerequisites. It simply lists supported file types without indicating scenarios where this tool is appropriate or any limitations.
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.
Our badge communicates server capabilities, safety, and installation instructions.
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