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get_ocr_languages

Lists supported languages for OCR text extraction in document conversion. Use this tool to identify available language options before processing documents with MinerU MCP Server.

Instructions

获取 OCR 支持的语言列表。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function 'get_ocr_languages' that calls the OCR language retrieval logic.
    async def get_ocr_languages() -> Dict[str, Any]:
        """获取 OCR 支持的语言列表。"""
        try:
            languages = get_language_list()
            return {"status": "success", "languages": languages}
        except Exception as e:
            return {"status": "error", "error": str(e)}
  • The helper function 'get_language_list' which retrieves the actual list of OCR languages.
    def get_language_list() -> List[Dict[str, str]]:
        """获取所有支持的语言列表。"""
        return LANGUAGES
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what the tool does (get a list) without any additional context about permissions, rate limits, response format, or other behavioral traits. This leaves significant gaps for a tool that likely returns structured data.

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 a single, efficient sentence in Chinese that directly states the tool's purpose. It is front-loaded with no wasted words, making it highly concise and well-structured for its simple function.

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

Completeness3/5

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

Given the tool's low complexity (0 parameters, simple read operation) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and a sibling tool, it could benefit from more context about usage or behavior to be fully complete.

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 tool has 0 parameters, and schema description coverage is 100% (since there are no parameters to describe). The description doesn't need to add parameter semantics, so it meets the baseline expectation. No compensation is required for missing parameter info.

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

Purpose4/5

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

The description clearly states the tool's purpose: '获取 OCR 支持的语言列表' (Get the list of languages supported by OCR). It specifies the verb '获取' (get) and resource 'OCR 支持的语言列表' (OCR-supported language list). However, it doesn't explicitly differentiate from its sibling tool 'parse_documents', which appears to be a different operation (parsing vs. listing).

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

Usage Guidelines2/5

Does 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. It doesn't mention the sibling tool 'parse_documents' or any other context for usage. The agent must infer usage based on the purpose alone, with no explicit when/when-not 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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