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Tarot MCP Server by RoxyAPI

by com.roxyapi

Yes or no answer - Yes no tarot reading API

post_tarot_yes_no
Read-only

Ask a specific question and receive a yes, no, or maybe answer based on a single tarot card draw. Upright cards indicate "Yes" with positive energy, reversed cards indicate "No" with caution, and certain inherently ambiguous cards (The Hanged Man, Wheel of Fortune, Temperance, Two of Swords, Four of Swords) return "Maybe" regardless of orientation since their energy signals pause, reflection, or shifting circumstances. Major Arcana cards give strong definitive answers, Minor Arcana cards give qualified nuanced answers. Returns the answer, strength level, drawn card details, and a contextual interpretation explaining why. Perfect for decision-making apps, quick guidance tools, fortune-telling chatbots, and interactive tarot experiences. Optionally provide a seed for reproducible answers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoResponse language (BCP 47). Supported: en, tr, de, es, hi, pt, fr, ru, zh-Hans, zh-Hant. Defaults to en. Coverage varies by domain, and a field with no translation in the requested language returns English.en
seedNoOptional seed for reproducible results. Same seed + same question = same answer. Useful for testing, sharing readings, or ensuring consistency. Omit for random draws each time.
compactNoSet true for the same data in a compact shape: arrays of same-shaped objects arrive columnar as {"__cols":[names],"__rows":[[values]]}. Lossless, typically 40 to 52 percent fewer tokens.
questionNoYour specific yes/no question. Be clear and focused. Good: "Should I move to a new city?" Bad: "What should I do about my life?" The more specific the question, the more useful the tarot guidance.

Schema Changelog

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

  1. Changed2 schema fields changed
    • changedInput schema / properties / lang / description
      Previous value: -"Response language (ISO 639-1). Supported: en, tr, de, es, hi, pt, fr, ru. Defaults to en. Languages without translations yet return English."New value: +"Response language (BCP 47). Supported: en, tr, de, es, hi, pt, fr, ru, zh-Hans, zh-Hant. Defaults to en. Coverage varies by domain, and a field with no translation in the requested language returns English."
    • changedInput schema / properties / lang / enum
      Previous value: -[
-  "en",
-  "tr",
-  "de",
-  "es",
-  "hi",
-  "pt",
-  "fr",
-  "ru"
-]New value: +[
+  "en",
+  "tr",
+  "de",
+  "es",
+  "hi",
+  "pt",
+  "fr",
+  "ru",
+  "zh-Hans",
+  "zh-Hant"
+]
  2. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {}
+]
    • changedInput schema / properties / compact / description
      Previous value: -"Set true to receive the exact same data in a token-optimized shape that is cheaper for you to read: whitespace is stripped and every array of same-shaped objects is encoded columnar as {\"__cols\":[field names],\"__rows\":[[values]]}, so each field name is sent once instead of once per row. Fully lossless (no field or value is dropped or changed) and typically 40 to 52 percent fewer tokens on large results. Prefer true whenever token or inference cost matters. Default false returns standard indented JSON."New value: +"Set true for the same data in a compact shape: arrays of same-shaped objects arrive columnar as {\"__cols\":[names],\"__rows\":[[values]]}. Lossless, typically 40 to 52 percent fewer tokens."
  3. Changed1 schema field changed
    • changedInput schema / properties / seed / example
      Previous value: -"optional-seed"New value: +"reading-2f9c1a"
  4. Changed1 schema field changed
    • changedInput schema / properties / compact / description
      Previous value: -"Return the same data in a token-optimized compact shape (minified, with same-shaped arrays encoded columnar) to reduce LLM token cost. Lossless: no fields are dropped. Default false."New value: +"Set true to receive the exact same data in a token-optimized shape that is cheaper for you to read: whitespace is stripped and every array of same-shaped objects is encoded columnar as {\"__cols\":[field names],\"__rows\":[[values]]}, so each field name is sent once instead of once per row. Fully lossless (no field or value is dropped or changed) and typically 40 to 52 percent fewer tokens on large results. Prefer true whenever token or inference cost matters. Default false returns standard indented JSON."
  5. Changed1 schema field changed
    • addedInput schema / properties / compact
      Added value: +{
+  "default": false,
+  "description": "Return the same data in a token-optimized compact shape (minified, with same-shaped arrays encoded columnar) to reduce LLM token cost. Lossless: no fields are dropped. Default false.",
+  "type": "boolean"
+}
  6. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Despite readOnlyHint and destructiveHint already covering safety, the description goes well beyond annotations by explaining card orientation mapping, special ambiguous cards, Major vs Minor Arcana strength, return payload contents, and seed reproducibility. This gives agents accurate expectations for how the tool behaves.

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 front-loaded with the core behavior, then systematically covers interpretation rules, output structure, use cases, and seed behavior. Every sentence contributes unique information with no redundancy.

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

Completeness5/5

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

With no output schema, the description compensates by listing the returned components: answer, strength level, drawn card details, and interpretive explanation. All parameters are documented in the schema, and the behavioral rules are fully specified, making the tool callable without further research.

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 coverage is 100%, so the baseline is 3. The description adds slight value by explaining the seed's reproducibility and emphasizing question specificity, but it doesn't meaningfully expand on lang or compact beyond what the schema already documents.

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?

The description states a clear verb and resource: ask a specific question and receive a yes/no/maybe answer from a single tarot card draw. It also distinguishes itself from sibling tools by focusing on yes/no outcomes and single-card mechanics, making the purpose unmistakable.

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?

The description provides clear context for use: decision-making apps, quick guidance tools, chat bots, and interactive tarot experiences. It does not explicitly name alternatives or state when not to use it, so it falls just short of a 5.

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

A4.2/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: deck list/detail, daily draws, generic draws, four named spreads, custom spreads, and yes/no readings. Even the overlapping draw endpoints are distinguishable by their specific use cases.

Naming Consistency5/5

All tool names consistently follow a snake_case verb_tarot_resource pattern, which makes the toolset predictable and easy to navigate. The only minor oddity is get_tarot_cards_id, but it does not break the overall convention.

Tool Count5/5

Ten tools is an ideal size for a tarot API: two reference tools, one daily draw, one generic draw, four fixed spreads, one custom spread, and one yes/no tool. Each tool earns its place without overlap or bloat.

Completeness5/5

The surface covers the full tarot domain: browsing cards, retrieving detailed card interpretations, drawing cards, multiple popular spread types, custom spreads, and targeted yes/no guidance. There are no obvious dead ends or critical missing workflows.

Resources