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NiuTrans

MCP Document Parse

by NiuTrans
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined as parsing various document formats into Markdown, leaving no room for confusion or misselection.

    Naming Consistency5/5

    The single tool name 'parse_document_by_path' follows a clear verb_noun pattern, and since there are no other tools to compare against, it is inherently consistent. No naming conventions are mixed or violated.

    Tool Count2/5

    A single tool is too few for the server's purpose of document parsing, as it suggests a thin surface that may lack essential operations like handling different parsing modes, error recovery, or batch processing. This minimal count limits functionality and could lead to agent workarounds.

    Completeness2/5

    The tool set is severely incomplete for document parsing; it only offers parsing by file path without support for operations like parsing from URLs, handling different output formats, validating documents, or managing parsing errors. This creates significant gaps that will likely cause agent failures in real-world scenarios.

  • Average 3.9/5 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 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

  • Behavior3/5

    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 adds useful context beyond basic functionality: it specifies the file_path must be an absolute path (not relative), mentions it uses 'NiuTrans Document Api', and implies it's for reading/parsing (not editing). However, it doesn't cover potential errors, rate limits, authentication needs, or output behavior details.

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

    Conciseness4/5

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

    The description is appropriately sized and front-loaded, starting with the core functionality. However, the second sentence about prioritization could be integrated more smoothly, and the final API mention feels slightly tacked on. Overall, it's efficient with minimal waste.

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

    Completeness4/5

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

    Given the tool's moderate complexity (file parsing/conversion), no annotations, and the presence of an output schema (which handles return values), the description is reasonably complete. It covers purpose, usage priority, parameter nuance, and API context, though it could benefit from more behavioral details like error handling or limitations.

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

    Parameters3/5

    Does 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 single parameter (file_path) with its format support. The description adds marginal value by emphasizing the absolute path requirement and mentioning the API name, but doesn't provide additional syntax, examples, or constraints beyond what the schema states.

    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 tool's purpose with specific verbs ('Convert', 'reading') and resources ('PDF, Word, Excel, and PPT files', 'Markdown format'), including the conversion target format. It explicitly mentions the tool's scope (office files) and distinguishes it by labeling it as 'optimal' and 'should be prioritized', though no sibling tools exist for comparison.

    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 provides clear usage context by stating this is 'the optimal tool for reading such office files and should be prioritized for use', which gives strong guidance on when to use it. However, it lacks explicit alternatives or exclusions (e.g., when not to use it), and no sibling tools exist to differentiate from.

    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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