Skip to main content
Glama

Tarot MCP Server by RoxyAPI

by com.roxyapi

Three card spread, past present future - Tarot spread API

post_tarot_spreads_three_card
Read-only

Perform the classic three-card tarot spread revealing Past (what led to this situation), Present (current energy and circumstances), and Future (likely outcome if current path continues). The most popular beginner-friendly spread, perfect for quick insights, daily guidance, or exploring specific questions. Each position includes a drawn card with reversal state, keywords, full meaning, and position-specific interpretation. Returns a summary connecting all three cards. Ideal for tarot reading apps, decision-making tools, and personal growth platforms. Optionally provide a seed for reproducible readings.

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 3 cards in same positions. Useful for sharing readings, testing, or ensuring users get consistent results. Omit for random draws.
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.
questionNoOptional specific question to focus the reading. Examples: "What should I know about my relationship?", "How can I improve my finances?", "What is blocking my creative growth?" Leave empty for general 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

A4/5.0
Behavior4/5

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

Annotations already establish read-only and non-destructive behavior. The description adds useful behavioral detail: each position includes reversal state, keywords, full meaning, position-specific interpretation, and a connecting summary, plus reproducible results via seed. It does not cover all response-shape details, but the main behavioral characteristics are disclosed.

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

Conciseness3/5

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

The core behavior is front-loaded and the structure is logical, but the description includes some promotional filler such as 'perfect for quick insights' and 'Ideal for tarot reading apps, decision-making tools, and personal growth platforms.' These add context but are not strictly necessary.

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?

With no output schema, the description adequately explains what the caller receives: card per position with reversal state, keywords, meaning, position-specific interpretation, and a summary. It does not deeply address each parameter, but the schema already covers those. Overall it is sufficient for a low-complexity read-only tool.

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 all four parameters are already documented in the schema. The description adds only a brief mention of seeds and specific questions, which is useful but not substantial beyond what the schema provides. Baseline 3 is appropriate.

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 uses a specific verb and resource: 'Perform the classic three-card tarot spread' and immediately enumerates the three positions (Past, Present, Future). Its name and content clearly distinguish it from the other spread tools in the sibling list.

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 gives clear usage context: 'quick insights, daily guidance, or exploring specific questions' and labels it 'beginner-friendly.' It does not explicitly contrast it with sibling spreads like career, love, or celtic cross, so exclusions are absent, but the context is strong enough for selection.

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

All Tarot MCP Server by RoxyAPI toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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