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aadilr

ChangeThisFile MCP Server

by aadilr
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one performs file conversions, the other lists supported conversion routes. No overlap exists.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern (convert_file, list_conversions) using snake_case, making naming predictable.

    Tool Count3/5

    With only 2 tools, the server feels minimal for a file conversion service. While covering the core functionality, the low count suggests a thin surface.

    Completeness3/5

    The server covers basic conversion and format discovery, but lacks features like conversion history, batch processing, or progress tracking, leaving notable gaps.

  • Average 4.4/5 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
    • 4 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.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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?

    Annotations already declare readOnlyHint=true, so the description need not restate safety. The description adds the filtering behavior, which is useful but not extensive behavioral context.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    Two sentences efficiently communicate the purpose and optional filter, with zero unnecessary words. Front-loaded with the main action.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a simple tool with one optional parameter and no output schema, the description fully covers what the agent needs to know: what it lists and how to filter.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema coverage is 100% with the parameter already described, but the description adds meaning by explaining the filter effect and providing an example ('docx' returns all DOCX target options), enhancing understandability.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the verb 'list' and resource 'supported conversion routes', and implicitly distinguishes from sibling 'convert_file' by indicating this tool provides options for conversion rather than performing the conversion.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    It specifies when to use the tool (to list conversion routes, optionally filtered by source format) and gives a concrete example. However, it does not explicitly state when not to use it or mention alternatives beyond the sibling.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    The description discloses key behavioral details: returns a temporary download URL (valid 1 hour) and that the file is deleted within 24 hours. These details are beyond what annotations provide (readOnlyHint=false, destructiveHint=false) and give the agent important lifecycle information. No contradiction with annotations exists.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is concise at 3 sentences, each serving a distinct purpose: stating the core action, specifying parameter rules, and detailing the return behavior. No extraneous information is included, making it easy for an agent to parse quickly.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given no output schema, the description adequately explains the return format (temporary URL with expiry) and data retention. It covers all input modalities and constraints. The presence of sibling tool name provides context. The description is complete for a conversion tool of moderate complexity.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The input schema already describes all 5 parameters (100% coverage), setting baseline at 3. The description adds semantic value by explaining the mutual exclusivity of source_url and base64_content, specifying the ~5MB limit for base64, and noting that source_format can be auto-detected. This enhances the agent's understanding beyond the schema's per-parameter descriptions.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description begins with a clear verb-resource pair: 'Convert a file from one format to another.' This immediately identifies the tool's core function. It also distinguishes itself from the sibling tool 'list_conversions' by focusing on performing the conversion rather than listing available formats.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description explicitly states the two mutually exclusive input methods (url vs base64) and clarifies that exactly one is required. It provides guidance on when to prefer each (URL for large files, base64 for small files) and mentions auto-detection of source format. However, it does not explicitly state when not to use this tool or compare it to alternatives beyond the sibling.

    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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  • Evaluate tool definition quality.

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