boltwork-mcp

extract_data

Extract structured data from PDFs: document type, dates, parties, amounts, line items, and reference numbers. Ideal for invoices, contracts, receipts, and forms.

Instructions

Extract structured data from a PDF document. Returns document type, dates, parties, amounts, line items, and reference numbers. Costs 200 sats via Lightning. Use for: invoices, contracts, receipts, forms.

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": {
      "url": "<url>"
    },
    "name": "extract_data"
  }
}

Input Schema

Name	Required	Description	Default
`url`	Yes	URL of the PDF
`max_pages`	No	Max pages to process (default 20)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.22May 28, 2026

TDQS

A4/5.0

Behavior3/5

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

No annotations exist, so description must cover behavioral traits. Mentions cost (200 sats via Lightning) which is useful. Does not mention read-only nature, side effects, or authentication requirements. Lacks depth but avoids contradictions.

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?

Two sentences with no wasted words. First sentence states action and output, second sentence adds cost and usage scope. Front-loaded and 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 two simple parameters and no output schema, the description explains purpose, output categories, cost, and use cases. Could be improved by describing output format or error handling, but overall sufficient for basic selection.

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?

Input schema has 100% coverage with descriptions for both parameters. Description adds no additional parameter-level details beyond the schema, and does not clarify default behavior or constraints. Baseline score of 3 applies.

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?

Clearly states it extracts structured data from PDF, lists specific return fields (document type, dates, etc.) and use case examples (invoices, contracts, receipts, forms). Distinguishes from siblings like extract_tables and summarise_pdf.

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

Usage Guidelines4/5

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

Provides explicit use cases ('Use for: invoices, contracts, receipts, forms'), giving clear context for when to use. Does not explicitly state when not to use or name alternatives, but the examples imply appropriate scenarios.

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

Deploy Server