Tarot MCP Server by RoxyAPI

Career spread, 7 cards - Career tarot reading API

post_tarot_spreads_career

Read-only

Perform a comprehensive 7-card career tarot spread using SWOT analysis framework (Strengths, Weaknesses, Opportunities, Threats) for professional guidance, business decisions, and vocational clarity. This career-focused reading examines seven strategic business aspects: Current Situation (your present professional position and workplace energy), Strengths (your professional assets, talents, and competitive advantages), Weaknesses (areas needing development, skill gaps, or limiting beliefs), Opportunities (potential growth paths, new ventures, or doors opening), Threats (obstacles, competition, or external challenges), Advice (actionable guidance for navigating your career path), and Outcome (where your professional journey is heading if you follow the guidance). Perfect for career coaching platforms, professional development apps, business consulting tools, job search websites, entrepreneurship platforms, and executive coaching services. Use for career transitions, job offers evaluation, promotion decisions, starting a business, workplace conflicts, finding your calling, or strategic career planning. Combines traditional tarot wisdom with modern SWOT business analysis for practical professional insight. Ideal for employees, entrepreneurs, freelancers, career changers, and anyone seeking vocational direction.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`lang`	No	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.	en
`seed`	No	Optional seed for reproducible results. The same seed always draws the same seven cards into the same career positions, which is what lets a reading be shared or re-rendered. Omit for a random draw.
`compact`	No	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.
`question`	No	Optional querent question to focus the career spread. It is echoed back on the reading and gives the seven career positions their context. Omit for general work and vocation guidance.

Schema Changelog

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

Changed2 schema fields changedAug 25, 2026

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"
+]

Changed2 schema fields changedAug 17, 2026

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."

Changed2 schema fields changedAug 5, 2026

changedInput schema / properties / question / description

Previous value: -"Optional querent question to focus the career spread. It is echoed back on the reading and gives the five career positions their context. Omit for general work and vocation guidance."New value: +"Optional querent question to focus the career spread. It is echoed back on the reading and gives the seven career positions their context. Omit for general work and vocation guidance."

changedInput schema / properties / seed / description

Previous value: -"Optional seed for reproducible results. The same seed always draws the same five cards into the same career positions, which is what lets a reading be shared or re-rendered. Omit for a random draw."New value: +"Optional seed for reproducible results. The same seed always draws the same seven cards into the same career positions, which is what lets a reading be shared or re-rendered. Omit for a random draw."

Changed3 schema fields changedAug 2, 2026

addedInput schema / properties / question / description

Added value: +"Optional querent question to focus the career spread. It is echoed back on the reading and gives the five career positions their context. Omit for general work and vocation guidance."

addedInput schema / properties / seed / description

Added value: +"Optional seed for reproducible results. The same seed always draws the same five cards into the same career positions, which is what lets a reading be shared or re-rendered. Omit for a random draw."

changedInput schema / properties / seed / example

Previous value: -"optional-seed"New value: +"reading-2f9c1a"

Changed1 schema field changedJul 22, 2026

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."

Changed1 schema field changedJul 22, 2026

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"
+}

First observedJul 8, 2026

TDQS

A3.7/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so no side-effect warning is needed. The description adds functional context such as the seven SWOT positions, but it does not describe response shape, pagination, rate limits, or reproducibility; seed behavior is left to the parameter schema.

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 first sentence is a strong front-loaded summary. However, the description repeats career and use-case positioning across several clauses ('Perfect for...', 'Use for...', 'Ideal for...') and includes promotional filler like 'practical professional insight,' which does not earn its place for an agent deciding whether to call the tool.

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?

The description covers the conceptual scope and common use cases well, and annotations cover safety. But with no output schema, it does not state what shape the response will take, and it omits any direct statement of the return value; these gaps keep it from being fully complete.

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 input schema provides descriptions for all four parameters, including enum values, defaults, and examples, so schema coverage is 100%. The tool description adds no parameter-level detail, making the baseline 3 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 opens with a specific verb and resource: 'Perform a comprehensive 7-card career tarot spread using SWOT analysis framework.' The career domain and seven named positions clearly set it apart from sibling spreads such as love, celtic_cross, and three_card.

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?

It explicitly lists concrete triggers: 'Use for career transitions, job offers evaluation, promotion decisions, starting a business, workplace conflicts...' This gives clear context for when the tool is appropriate. It does not mention when to prefer a sibling tool or provide exclusions, so it stops short of full routing guidance.

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

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