Vedic Astrology and Kundli MCP Server by RoxyAPI

Get KP-Newcomb ayanamsa - Dynamic daily calculation

get_vedic_astrology_kp_ayanamsa

Read-only

Get the KP-Newcomb (Krishnamurti) ayanamsa for any instant, computed continuously from Newcomb precession theory rather than looked up in a preset table, so it tracks the exact moment you ask for instead of the calendar year. Supply date alone for midnight UTC, or add time and timezone to pin a birth moment exactly. This is the precession offset subtracted from a tropical longitude to obtain the sidereal one, and it is what makes a KP chart reproduce the reference software your practitioners already use. Returns the same value every KP endpoint applies internally. Use it as a dynamic KP Newcomb ayanamsa calculator when you need the Krishnamurti ayanamsa for today, for a birth moment, or for any instant a chart is being rectified against.

Input Schema

TableJSON Schema

Name	Required	Description
`date`	No	Date for ayanamsa calculation in YYYY-MM-DD format. Defaults to today if not provided. Ayanamsa changes by ~0.01 degrees per month due to the precession of Earth.
`time`	No	Time of day in 24-hour HH:MM:SS format, interpreted in the timezone below. Omit for midnight UTC. The ayanamsa moves about 0.14 arcseconds across a day, so supplying the time matters only when reconciling a chart against reference software to the arcsecond.
`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.
`timezone`	No	IANA name (e.g. "Asia/Kolkata", "America/New_York"), decimal hours (e.g. 5.5 for IST, -5 for EST), or a fixed UTC offset (e.g. "+05:30"). IANA resolved to the offset in force at the given date and the time field above. Defaults to 0 (UTC).

Output Schema

TableJSON Schema

Name	Required	Description	Default
`date`	Yes
`type`	Yes
`formula`	Yes
`instant`	Yes
`ayanamsa`	Yes
`calculated`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 20, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "ayanamsa": {
+      "type": "number"
+    },
+    "calculated": {
+      "type": "string"
+    },
+    "date": {
+      "type": "string"
+    },
+    "formula": {
+      "type": "string"
+    },
+    "instant": {
+      "type": "string"
+    },
+    "type": {
+      "type": "string"
+    }
+  },
+  "required": [
+    "date",
+    "instant",
+    "ayanamsa",
+    "type",
+    "formula",
+    "calculated"
+  ],
+  "type": "object"
+}

Changed1 schema field changedSep 16, 2026

changedInput schema / properties / timezone / description

Previous value: -"IANA name (e.g. \"Asia/Kolkata\", \"America/New_York\"), decimal hours (e.g. 5.5 for IST, -5 for EST), or a fixed UTC offset (e.g. \"+05:30\"). IANA resolved to the DST-correct offset for the given date. Applies to the time field above. Defaults to 0 (UTC)."New value: +"IANA name (e.g. \"Asia/Kolkata\", \"America/New_York\"), decimal hours (e.g. 5.5 for IST, -5 for EST), or a fixed UTC offset (e.g. \"+05:30\"). IANA resolved to the offset in force at the given date and the time field above. Defaults to 0 (UTC)."

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."

Changed1 schema field changedAug 1, 2026
- changedInput schema / properties / timezone / example
```
Previous value: -5.5New value: +"Asia/Kolkata"
```

Changed2 schema fields changedJul 31, 2026

addedInput schema / properties / time

Added value: +{
+  "description": "Time of day in 24-hour HH:MM:SS format, interpreted in the timezone below. Omit for midnight UTC. The ayanamsa moves about 0.14 arcseconds across a day, so supplying the time matters only when reconciling a chart against reference software to the arcsecond.",
+  "example": "09:00:00",
+  "format": "time",
+  "type": "string"
+}

addedInput schema / properties / timezone

Added value: +{
+  "description": "IANA name (e.g. \"Asia/Kolkata\", \"America/New_York\"), decimal hours (e.g. 5.5 for IST, -5 for EST), or a fixed UTC offset (e.g. \"+05:30\"). IANA resolved to the DST-correct offset for the given date. Applies to the time field above. Defaults to 0 (UTC).",
+  "example": 5.5,
+  "type": "string"
+}

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

A4.4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description does not need to repeat that. It adds valuable context: the ayanamsa is computed continuously rather than looked up, it tracks the exact moment, it is the precession offset subtracted from tropical longitude, and it returns the same value as all KP endpoints. This goes beyond the schema and annotations.

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?

The description is moderately long but every sentence contributes: purpose, calculation method, usage patterns, and relation to KP charts. It is front-loaded with the main purpose and then provides supporting detail. It could be trimmed slightly (e.g., the phrase 'dynamic daily calculation' in the title is redundant with the description), but overall it is well-structured and informative.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values are already documented. The description covers what the tool does, when to use it, how to provide inputs, and what the result represents. For a read-only tool with optional parameters, nothing essential is missing.

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 all four parameters have descriptions. The tool description adds extra nuance: it explains the effect of date ('changes by ~0.01 degrees per month') and time ('moves about 0.14 arcseconds across a day'), which helps agents understand precision requirements. This adds meaning beyond the schema alone.

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 clearly states it retrieves the KP-Newcomb ayanamsa for any instant, computed dynamically from precession theory. It distinguishes itself from any sibling by naming the specific ayanamsa variant and its calculation method, and no other tool in the sibling list targets ayanamsa, so differentiation is inherent.

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 explicitly says when to use it: 'Use it as a dynamic KP Newcomb ayanamsa calculator when you need the Krishnamurti ayanamsa for today, for a birth moment, or for any instant a chart is being rectified against.' It also explains how to supply date/time/timezone. It does not explicitly mention when not to use it, but since there are no alternative ayanamsa tools, this is not a significant gap.

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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