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mcp-docparser

mcp-docparser

by Jasonzld
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

extract_text

Pull readable text from PDFs, Word, Excel, and images, using OCR when needed. Provide a file path to get the content.

Instructions

Extract text from any document or image using OCR if needed

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": "extract_text"
  }
}

Input Schema

NameRequiredDescriptionDefault
file_pathYesPath to the document or image file

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

B3.1/5.0
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 behavioral burden. It doesn't state supported formats, whether extraction requires write output or returns inline, OCR language support, or failure behavior for unreadable files — significant gaps for a tool that may silently invoke a heavyweight OCR path.

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?

A single front-loaded sentence with no filler. Every clause ('any document or image', 'OCR if needed') carries information.

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?

For a one-parameter read tool this is minimally adequate: the agent knows what goes in and roughly what comes out. However, with no output schema and no annotation coverage, the absence of any note on return shape, supported file types, or OCR behavior leaves real gaps.

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?

Only one parameter exists and the schema already documents it at 100% coverage ('Path to the document or image file'). The description adds nothing beyond the schema, which is the baseline expectation at full coverage.

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?

States a specific verb (extract) and resource (text from documents/images), and notes the OCR fallback mechanism. It does not distinguish itself from siblings like parse_document, ocr_image, or batch_ocr, so an agent cannot tell when this is the right pick over those.

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 phrase 'using OCR if needed' implies automatic routing to OCR, but there is no guidance on when to choose this over ocr_image, parse_document, or batch_ocr, and no exclusions or prerequisites stated.

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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