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uuina

Mistral OCR MCP Server

by uuina

ocr_from_url

Extract Markdown text from public document or image URLs using OCR. Customize page range, table format, and image extraction.

Instructions

从公开的文档或图片 URL 中提取 Markdown 文本。

默认使用 "mistral-ocr-latest" 模型。
默认不提取图片。若需提取,需设置 include_images=True。

可调参数:
- url (str): 必填,目标文件或图片的公网 URL 地址。
- pages (str, 默认 ""): 指定需要提取的页码范围(如 "0-3"),为空表示提取所有页面。
- table_format (str, 默认 "markdown"): 表格输出格式。可选 "markdown"、"html" 或 None。
- include_images (bool, 默认 False): 是否提取图片。若开启,将返回图片信息。
- extract_header (bool, 默认 False): 是否专门解析并提取页眉。
- extract_footer (bool, 默认 False): 是否专门解析并提取页脚。
- image_limit (int, 默认 0): 限制单次提取的最大图片数量。
- image_min_size (int, 默认 0): 设置提取图片的最小尺寸限制(像素)。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
pagesNo
image_limitNo
table_formatNomarkdown
extract_footerNo
extract_headerNo
image_min_sizeNo
include_imagesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so description must compensate. It mentions default model, image extraction default, and lists parameters but lacks details on side effects, auth, or rate limits.

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 structured with a brief introduction and parameter list, avoiding fluff. Could be more compact but is reasonably concise.

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?

With 8 parameters and an output schema, the description covers parameter semantics adequately but misses usage context and output details (though output schema may compensate).

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

Parameters2/5

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

Schema description coverage is 0%, but the description provides explanations for each parameter. However, there is a contradiction: description says default include_images=False, but schema shows default true, reducing reliability.

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 extracts Markdown text from a public URL, listing key parameters and defaults. However, it does not distinguish from sibling tools like ocr_from_file or ocr_to_markdown_file.

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?

No explicit guidance on when to use this tool vs alternatives (e.g., file-based OCR). The description only implies URL usage.

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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