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uuina

Mistral OCR MCP Server

by uuina

ocr_from_file

Extracts Markdown text from local PDF, DOCX, PPTX, or image files. Supports page range selection, table format options, and image extraction.

Instructions

从本地文件或图片中提取 Markdown 文本并以字符串形式返回。

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:
- file_path (str): 必填,本地文档(如 PDF, PPTX, DOCX)或图片文件的绝对路径。
- 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
pagesNo
file_pathYes
image_limitNo
table_formatNomarkdown
extract_footerNo
extract_headerNo
image_min_sizeNo
include_imagesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Given no annotations, the description carries the full burden. It discloses defaults (model, include_images=False), parameter behaviors (header/footer extraction, image limits), and output format (Markdown string). However, it lacks details on error handling, rate limits, or required permissions, leaving some behavioral gaps.

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 well-structured: primary action first, then defaults, then parameter list. It is slightly long but every sentence adds value. Could be tightened by grouping related parameters, but remains efficient.

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 8 parameters, 1 required, and an output schema (not shown), the description covers all parameters and core behavior. It does not explicitly differentiate from siblings or detail return structure beyond 'Markdown text', but context is adequate for a single tool.

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

Parameters5/5

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

Schema coverage is 0%, so the description must fully explain parameters. It does so thoroughly: each parameter is described with purpose, default, and allowed values (e.g., table_format options). This adds significant meaning beyond the bare schema, enabling correct usage.

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 extracts Markdown text from local files or images. It distinguishes from sibling tools like ocr_from_url by specifying 'local file' and 'absolute path', leaving no ambiguity.

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

Usage Guidelines3/5

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

The description does not explicitly state when to use this tool versus alternatives (e.g., ocr_from_url for remote files). Usage context is implied by the tool name and file_path parameter, but no explicit guidance or exclusion criteria are provided.

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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