Numerology MCP Server by RoxyAPI

Calculate Personal Day - Daily numerology forecast API

post_numerology_personal_day

Read-only

Calculate the Personal Day number from a birth month and day with Pythagorean numerology, the 1 to 9 theme of a single calendar day personalized to the birthday. The day is targetDate, or today in UTC when omitted. The response returns the day theme and guidance with the parent Personal Month and Personal Year, in the language set by lang. Built for daily push notifications, morning briefings, calendar widgets 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
`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.
`targetDate`	No	Target date in YYYY-MM-DD format, in the years 100 to 2100. Defaults to today (UTC).

Output Schema

TableJSON Schema

Name	Required	Description	Default
`theme`	Yes
`guidance`	Yes
`targetDate`	Yes
`personalDay`	Yes
`personalYear`	Yes
`personalMonth`	Yes
`personalYearTheme`	Yes
`personalMonthTheme`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 1, 2026

changedInput schema / properties / targetDate / description

Previous value: -"Target date in YYYY-MM-DD format. Defaults to today (UTC)."New value: +"Target date in YYYY-MM-DD format, in the years 100 to 2100. Defaults to today (UTC)."

Changed1 schema field changedSep 20, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "guidance": {
+      "type": "string"
+    },
+    "personalDay": {
+      "type": "number"
+    },
+    "personalMonth": {
+      "type": "number"
+    },
+    "personalMonthTheme": {
+      "type": "string"
+    },
+    "personalYear": {
+      "type": "number"
+    },
+    "personalYearTheme": {
+      "type": "string"
+    },
+    "targetDate": {
+      "type": "string"
+    },
+    "theme": {
+      "type": "string"
+    }
+  },
+  "required": [
+    "personalDay",
+    "theme",
+    "guidance",
+    "targetDate",
+    "personalMonth",
+    "personalMonthTheme",
+    "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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so it is clear this is a safe read. The description adds useful behavior beyond that: targetDate defaults to today in UTC, and the response bundles the day theme with the parent Personal Month and Personal Year. Errors, rate limits, and failure modes remain unaddressed.

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 core purpose, then mechanics (default date, response contents), then use cases. No sentence is wasted and it never buries the lead. Slightly long, but every clause carries information.

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 an output schema present and 100% schema coverage, the description needn't explain return values, yet it usefully summarizes the response shape. For a 5-parameter read-only calculation tool this is essentially complete, missing only edge-case or error behavior.

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 defaults, ranges, and the lang enum are already fully documented in the schema. The description restates the targetDate default (today UTC) and the lang-driven output language, which is consistent but adds little beyond structured fields, so the baseline 3 applies.

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 Day number'), plus the exact inputs (birth month/day) and the personality of the output (1-9 theme of a calendar day). It is distinguishable from siblings like personal_month, personal_year, and daily that could otherwise be confused with it.

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?

The 'Built for daily push notifications, morning briefings, calendar widgets and AI agents' clause gives real deployment context, implying when this tool fits. However, it never names the adjacent siblings (personal_month, personal_year, daily) or states when NOT to use this tool, so the agent must infer the boundary itself.

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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