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ocr-receipts-biz

OCR receipts to structured JSON [x402: 0.05 USDC on Base, pay-per-use]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesentrada

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It does disclose a key behavioral trait: it is a paid tool with a specific cost of 0.05 USDC on Base via x402. However, it does not explain authentication, payment flow, input format constraints, rate limits, or side effects beyond charging.

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 concise sentence with zero wasted words. The core function is front-loaded, and the pricing detail is compactly appended in brackets.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a paid OCR tool with one required parameter and no output schema, the description is not complete enough. An agent would not know how to format the input, what fields the structured JSON contains, or how the x402 payment is initiated. The relevant sibling set includes many similar OCR tools, so more distinguishing context is needed.

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?

The schema has 100% description coverage, so the baseline is 3. The description adds some meaning by implying that the 'input' parameter should be a receipt, but it does not specify whether that input is an image URL, file path, base64, or text. The schema's own description, 'entrada,' provides essentially no additional clarity.

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?

The description clearly states the verb and resource: OCR receipts to structured JSON. It is distinct from generic OCR tools due to the receipt focus and output format, but it does not explicitly differentiate itself from closely related siblings like ocr-receipts or ocr-receipts-biz2.

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 description provides no guidance on when to use this tool over alternatives. It only mentions the pay-per-use price, leaving the agent to infer that this is the paid receipt-OCR option, with no explicit when-to-use or when-not-to-use instructions.

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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TDQS

C2.6/5.0
Disambiguation1/5

The set contains many trivially indistinct tools: ai-inference/inference, compress/comprimir, count-tokens/contar-tokens, detect-language/language-detect, and multiple overlapping OCR receipt variants. With 160 tools and pairs that differ only by language or suffix, an agent cannot reliably distinguish several capabilities.

Naming Consistency3/5

Most names are readable lower-hyphen identifiers, but they mix action verbs, noun phrases, domain prefixes, pipeline suffixes, Spanish/English, and arbitrary demo/batch labels. There is a loose convention, but no consistent verb_noun pattern.

Tool Count1/5

160 tools on one server is an extreme count and clearly unwieldy. Even as a marketplace, exposing every variant, demo, and composed bundle as a top-level MCP tool overwhelms agent selection and adds little distinct capability.

Completeness3/5

The set covers a huge range of text, image, audio, code, market, compliance, and content-workflow tasks, so many intents have some available tool. However, it is a grab-bag rather than a defined service surface, and the arbitrary demo/specialized variants make it unclear whether a needed operation truly exists or is just a duplicate.

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