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PDF RAG MCP Server

PDF RAG MCP Server

by MBaranekTech
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

pdf_extract_tables

Extract tables from a specific PDF page and return them as markdown for use in RAG pipelines.

Instructions

Extract tables from a specific page of a PDF and return them as markdown.

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>",
      "page_num": "<page_num>"
    },
    "name": "pdf_extract_tables"
  }
}

Input Schema

NameRequiredDescriptionDefault
page_numYesPage number to extract tables from (1-indexed).
file_pathYesAbsolute path to the PDF file.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
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 states the read-like action and markdown return format, but does not disclose what happens if the page has no tables, if the page number is out of range, whether the file is modified, or any error behavior. For a tool with no annotation coverage, this is a notable gap.

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 sentence with no filler. It front-loads the primary action and resource, then states the output format. Every word earns its place.

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?

The tool has a complete input schema and an output schema, so the agent has enough structural information to invoke it correctly. The main missing context is edge-case behavior (no tables found, invalid page number) and explicit usage guidance, but for a simple extraction tool the description is largely sufficient.

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 both file_path and page_num are already documented in the schema, including page_num being 1-indexed. The description does not add extra parameter meaning beyond mentioning 'specific page', but it does not need to because the schema handles it.

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 uses a specific verb ('Extract tables'), identifies the exact resource ('from a specific page of a PDF'), and states the output format ('as markdown'). This clearly distinguishes it from siblings like pdf_get_page or pdf_search, which have different purposes.

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 when to use the tool: when you need tables from a PDF page. However, it provides no explicit guidance about when not to use it or which sibling tool might be better for other PDF-related tasks, such as pdf_search or pdf_get_page.

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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