Numerology MCP Server by RoxyAPI

Calculate Personal Month - Monthly numerology forecast API

post_numerology_personal_month

Read-only

Calculate the Personal Month number from a birth month and day with Pythagorean numerology, the 1 to 9 theme of one calendar month inside the Personal Year. The year and month are the ones sent, each defaulting to the current UTC year and month when omitted. The response returns the month theme, practical focus and the parent Personal Year with its theme, in the language set by lang. Built for monthly forecast features, push notifications, editorial columns and AI agents.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`day`	Yes	Birth day (1-31)
`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
`year`	No	Target year. Defaults to the current UTC year.
`month`	Yes	Birth month (1-12)
`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.
`targetMonth`	No	Target calendar month to forecast (1 to 12). Defaults to the current UTC month.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`focus`	Yes
`theme`	Yes
`personalYear`	Yes
`calendarMonth`	Yes
`personalMonth`	Yes
`personalYearTheme`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedOct 1, 2026

changedInput schema / properties / targetMonth / description

Previous value: -"Target calendar month to forecast (1-12, defaults to current month)"New value: +"Target calendar month to forecast (1 to 12). Defaults to the current UTC month."

changedInput schema / properties / year / description

Previous value: -"Target year for calculation (defaults to current year)"New value: +"Target year. Defaults to the current UTC year."

Changed1 schema field changedSep 30, 2026
- changedInput schema / properties / year / minimum
```
Previous value: -2020New value: +100
```

Changed1 schema field changedSep 20, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "calendarMonth": {
+      "type": "number"
+    },
+    "focus": {
+      "type": "string"
+    },
+    "personalMonth": {
+      "type": "number"
+    },
+    "personalYear": {
+      "type": "number"
+    },
+    "personalYearTheme": {
+      "type": "string"
+    },
+    "theme": {
+      "type": "string"
+    }
+  },
+  "required": [
+    "personalMonth",
+    "theme",
+    "focus",
+    "calendarMonth",
+    "personalYear",
+    "personalYearTheme"
+  ],
+  "type": "object"
+}

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: +[
+  {
+    "day": 18,
+    "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."

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

A3.9/5.0

Behavior4/5

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

With readOnlyHint=true and destructiveHint=false already covering safety, the description adds real context: year/month default to the current UTC year/month when omitted, the response returns month theme, practical focus and the parent Personal Year, and lang controls output language. It does not mention rate limits or caching, but the added behavioral detail is substantial.

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?

Four front-loaded sentences covering definition, defaults, response contents and audience; the definition leads and nothing is padding, though the closing audience list is the weakest-earning sentence.

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?

For a read-only calculation tool with a full output schema and 100% schema coverage, the description supplies the extra defaults, output shape and language-fallback behavior an agent needs. Sibling differentiation and target-vs-birth month disambiguation are the remaining gaps.

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 the baseline is 3. The description clarifies that year/month default to current UTC and that lang sets the response language, but it does not resolve the potential confusion between the required birth 'month' and the 'targetMonth' forecast parameter.

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?

States a specific verb (Calculate) and resource (Personal Month number) with the algorithm (Pythagorean) and the exact output contents (1 to 9 theme of a calendar month inside the Personal Year). It naturally distinguishes itself from siblings like post_numerology_personal_day and post_numerology_personal_year by naming the parent Personal Year relationship.

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?

Offers use-case framing ('monthly forecast features, push notifications, editorial columns and AI agents') but never states when to choose this over personal_day or personal_year, nor any prerequisite or exclusion. Usage is implied by the theme, not routed.

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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