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io.github.Xvvln/pdf-reader-mcp

io.github.Xvvln/pdf-reader-mcp

by Xvvln
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_pdf_annotations

Extract annotations such as comments, highlights, and underlines from PDF files. Optionally specify a page range to retrieve annotation details including page number, type, content, and author.

Instructions

获取PDF中的注释（批注、高亮、下划线等）。

Args: file_path: PDF文件的完整路径 pages: 要提取的页码范围（可选，默认全部页面）

Returns: 包含以下信息的字典: - total_annotations: 注释总数 - annotations: 注释列表，每个包含: - page: 页码 - type: 注释类型 - content: 注释内容 - author: 作者

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "file_path": "<file_path>"
    },
    "name": "get_pdf_annotations"
  }
}

Input Schema

NameRequiredDescriptionDefault
pagesNo
file_pathYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A4.1/5.0
Behavior3/5

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

No annotations are provided, so the description carries full burden. It describes the return format and parameters but does not disclose potential side effects, authorization needs, or rate limits. It is adequate but not rich.

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 and well-structured, using bullet points for arguments and returns. Every sentence adds value without redundancy.

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 thoroughly explains the return dictionary structure. Parameter descriptions are sufficient, and the tool fits clearly among PDF siblings. It is complete for the tool's 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?

Schema coverage is 0%, so the description must compensate. It explains file_path as full path and pages as optional range with default all pages. This adds meaning beyond the bare schema, meeting the baseline for low coverage.

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 it annotates PDF files (getting 批注、高亮、下划线等). It uses a specific verb and resource, and distinguishes from sibling tools like get_pdf_info or read_pdf_as_text by focusing solely on annotations.

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 implies usage for extracting annotations but does not explicitly state when to use it versus alternatives, nor does it mention prerequisites or exclusions. It lacks guidance on context.

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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