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crypto-payments-2026

INDUSTRY REPORT: Estado de los pagos cripto 2026 (deep, cited). input=optional scope. B2B: PSPs y comercios evalúan integrar pagos cripto. [x402: 120.0 USDC on Base, pay-per-use]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesservice input

Schema Changelog

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

  1. Added

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral disclosure burden. It discloses that the report is deep and cited and includes pay-per-use pricing, which is useful. However, it claims 'input=optional scope' while the schema marks the input parameter as required, and it does not describe the response format, citation mechanism, or any operational side effects. This contradiction undermines trust.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the report type and subject, followed by audience and billing metadata. There is almost no wasted text, though the dense mixed-language formatting and embedded pricing metadata make it slightly less clean than ideal.

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 single-parameter report tool, the description gives enough to understand the topic, depth, citation quality, audience, and cost. But without an output schema, it does not specify the return structure, and the optional/required input mismatch leaves the invocation contract unclear. It is minimally complete but not fully dependable.

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 only says 'service input', which is generic, but the description adds that input is an optional scope selector, giving it semantic meaning. However, 'optional' conflicts with the schema's required flag, so the added meaning is partially unreliable. Schema coverage is high, so the baseline of 3 applies despite the limited parameter detail.

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 identifies this as an industry report on the state of crypto payments in 2026, with explicit depth and citation markers. It names a specific resource and verb ('INDUSTRY REPORT') and states the B2B audience. It does not explicitly differentiate itself from overlapping siblings like x402-payments-landscape or latam-fintech-report, so it stops short of a 5.

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 gives an implied use case: B2B PSPs and merchants evaluating crypto payment integration. However, it does not say when to prefer this tool over siblings, nor does it provide exclusions or alternative tool guidance. The usage context is present but not explicit enough to route an agent reliably.

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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