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Numerology MCP Server by RoxyAPI

by com.roxyapi
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Calculate Personal Year - Personal Year number forecast API

post_numerology_personal_year
Read-only

Calculate the Personal Year number from a birth month and day with Pythagorean numerology, the 1 to 9 cycle that sets the theme of a calendar year. The year is the one sent, or the current UTC year when omitted, and it turns over on 1 January; the birth year is not needed. The response returns the place in the nine-year cycle, the theme, a forecast, opportunities, challenges and advice in the language set by lang. Built for yearly planning features, New Year content, coaching tools and AI agents.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dayYesBirth day (1-31)
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
yearNoYear to forecast. Defaults to the current UTC year; the Personal Year turns over on 1 January.
monthYesBirth month (1-12)
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.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
cycleYes
themeYes
adviceYes
forecastYes
challengesYes
personalYearYes
opportunitiesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / year / description
      Previous value: -"Year to calculate (defaults to current year)"New value: +"Year to forecast. Defaults to the current UTC year; the Personal Year turns over on 1 January."
  2. Changed1 schema field changed
    • changedInput schema / properties / year / minimum
      Previous value: -2020New value: +100
  3. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "advice": {
+      "type": "string"
+    },
+    "challenges": {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "cycle": {
+      "type": "string"
+    },
+    "forecast": {
+      "type": "string"
+    },
+    "opportunities": {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "personalYear": {
+      "type": "number"
+    },
+    "theme": {
+      "type": "string"
+    }
+  },
+  "required": [
+    "personalYear",
+    "cycle",
+    "theme",
+    "forecast",
+    "opportunities",
+    "challenges",
+    "advice"
+  ],
+  "type": "object"
+}
  4. 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"
+]
  5. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "day": 15,
+    "month": 7
+  }
+]
    • 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."
  6. 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."
  7. 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"
+}
  8. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already establish a safe read-only, non-destructive operation, and the description adds genuinely useful behavior beyond them: the year defaults to the current UTC year, the cycle turns over on 1 January, and the birth year is not required. It stops short of describing any limits or edge cases, but the added context is solid for a read-only calculation.

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?

Front-loaded with the calculation and cycle definition, then defaults, then output, then audience. It is slightly padded by the closing marketing sentence ('Built for yearly planning features...') which adds little operational value, but overall the structure is disciplined.

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 a full schema and an output schema present, the description need not enumerate return fields, yet it does outline theme, forecast, opportunities, challenges and advice, which orients the agent ahead of the structured response. The only real gap is the lack of disambiguation from the sibling month/day tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema carries the baseline burden, and the description adds real meaning on top: it clarifies the year default and turnover semantics and explicitly notes that no birth year is needed. The enums and compact/lossless shape are left to the schema, which is the right place for them.

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?

States a specific verb and resource ('Calculate the Personal Year number from a birth month and day') and scopes it to a 1-9 annual cycle, so the agent knows exactly what is computed. It does not, however, differentiate itself from the very close siblings post_numerology_personal_month and post_numerology_personal_day, leaving the agent to infer the scope boundary.

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?

Usage is only implied through audience framing ('yearly planning features, New Year content, coaching tools'), which hints at context but never states when to choose this over personal_month/personal_day or what inputs are disallowed. No alternatives or exclusions are named.

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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