Skip to main content
Glama

extract_pdf

Extract text and metadata from PDF documents. Supports page-specific extraction and returns structured content. Price: $0.004

Input Schema

NameRequiredDescriptionDefault
urlYesThe URL to process
pagesNoPage numbers to extract (omit for every page)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / pages / example
      Previous value: -[
      -  1,
      -  2,
      -  3
      -]New value: +[
      +  1,
      +  2
      +]
    • changedInput schema / properties / url / example
      Previous value: -"https://example.com/document.pdf"New value: +"https://raw.githubusercontent.com/mozilla/pdf.js-sample-files/master/tracemonkey.pdf"
  2. Changed4 schema fields changed
    • addedInput schema / properties / pages
      Added value: +{
      +  "description": "Page numbers to extract (omit for every page)",
      +  "example": [
      +    1,
      +    2,
      +    3
      +  ],
      +  "items": {
      +    "minimum": 1,
      +    "type": "number"
      +  },
      +  "type": "array"
      +}
    • changedInput schema / properties / url / description
      Previous value: -"URL of the PDF to extract"New value: +"The URL to process"
    • addedInput schema / properties / url / example
      Added value: +"https://example.com/document.pdf"
    • addedInput schema / properties / url / format
      Added value: +"uri"
  3. First observed

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the disclosure burden. It usefully states that it returns structured content and discloses a price ($0.004), which is real behavioral context. However, it omits limits (file size, page count), auth or URL constraints, and failure behavior for an external-URL-driven tool.

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?

Three short sentences, front-loaded with the core purpose before the optional capability and pricing. Every sentence carries distinct information with no redundancy or filler.

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?

No output schema exists, so the description's vague 'returns structured content' is the only return-value signal and leaves the structure undefined. With only two simple parameters and no annotations, the description is adequate but does not address extraction limits or error behavior an agent would need.

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 'url' and 'pages' are already documented in the schema. The description's reference to 'page-specific extraction' aligns with the pages parameter but adds no syntax or default detail beyond the schema's own 'omit for every page' note. Baseline 3 applies when the schema does the heavy lifting.

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 and resource: 'Extract text and metadata from PDF documents', which clearly identifies the operation and input type. It distinguishes itself from generic siblings like extract_data or get_contents by scoping to PDF documents, though it doesn't explicitly name an alternative. Clear and unambiguous.

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 guidance on when to choose this over siblings such as extract_data, get_contents, or fetch_webpage. The mention of 'page-specific extraction' hints at a use case but provides no conditions or exclusions for selecting this tool. The agent must infer usage entirely.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.