Vedic Astrology and Kundli MCP Server by RoxyAPI

Get KP planets at time intervals

post_vedic_astrology_kp_planets_interval

Read-only

Calculate positions of all 9 planets (Sun through Saturn, Rahu, Ketu) at regular time intervals with full KP hierarchy: sign lord, star lord, sublord, and sub-sublord. Returns longitude, zodiac sign, nakshatra, sublord, sub-sublord, and KP number (1-249) for each planet at each timestamp. Ideal for tracking planetary motion, finding optimal muhurta windows, analyzing transit patterns, and building KP ephemeris tables. Maximum range of 7 days with 15-minute to 24-hour intervals.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`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.
`ayanamsa`	No	Ayanamsa system for sidereal conversion. "kp-newcomb" uses the KP-Newcomb dynamic formula, the most common choice for KP astrology. "kp-old" uses the Krishnamurti original table from KP Reader-1 with constant precession rate. "lahiri" uses Lahiri/Chitrapaksha ayanamsa, matching most traditional Vedic software. "raman" uses the B.V. Raman ayanamsa from Hindu Predictive Astrology, a recognised traditional school that sits about 1.45 degrees below Lahiri. Defaults to "kp-newcomb".	kp-newcomb
`latitude`	Yes	Observer latitude in decimal degrees (for future Lagna calculations)
`nodeType`	No	Lunar node convention. "mean" is the smoothed average node, which always moves retrograde; "true" is the osculating node, which tracks the real perturbed node, oscillates up to about 1.5 degrees either side of the mean on a 173-day cycle, and can briefly turn direct. Neither is more correct and they almost always fall in the same sign. Applies to the Rahu and Ketu positions. Mean is the traditional Vedic default and what printed panchangs use; the choice can move a KP sub-lord in narrow boundary cases, where a span can be as small as 0.5 degrees. Defaults to "mean".	mean
`timezone`	No	IANA name (e.g. "America/New_York", "Europe/London") OR decimal hours from UTC. IANA resolved to the DST-correct offset for the startDatetime date. When non-zero, all datetimes are treated as local time in this timezone (Z suffix is ignored). Defaults to 0 (UTC).
`longitude`	Yes	Observer longitude in decimal degrees (for future Lagna calculations)
`endDatetime`	Yes	End datetime in ISO 8601 (YYYY-MM-DDTHH:MM:SS). Maximum 7 days from start. Interpreted as local time when a non-zero timezone is provided (a trailing Z is accepted but ignored); with timezone 0 it is UTC.
`startDatetime`	Yes	Start datetime in ISO 8601 (YYYY-MM-DDTHH:MM:SS). Interpreted as local time when a non-zero timezone is provided (a trailing Z is accepted but ignored); with timezone 0 it is UTC.
`intervalMinutes`	Yes	Time between calculations in minutes. Range: 15 (quarter-hourly) to 1440 (daily).

Output Schema

TableJSON Schema

Name	Required	Description	Default
`ayanamsa`	Yes
`intervals`	Yes
`endDatetime`	Yes
`ayanamsaValue`	Yes
`startDatetime`	Yes
`totalIntervals`	Yes
`intervalMinutes`	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": "string"
+    },
+    "ayanamsaValue": {
+      "type": "number"
+    },
+    "endDatetime": {
+      "type": "string"
+    },
+    "intervalMinutes": {
+      "type": "number"
+    },
+    "intervals": {
+      "items": {
+        "properties": {
+          "date": {
+            "type": "string"
+          },
+          "datetime": {
+            "type": "string"
+          },
+          "planets": {
+            "additionalProperties": {
+              "properties": {
+                "degreeInSign": {
+                  "type": "number"
+                },
+                "isRetrograde": {
+                  "type": "boolean"
+                },
+                "kpNumber": {
+                  "type": "number"
+                },
+                "longitude": {
+                  "type": "number"
+                },
+                "nakshatra": {
+                  "type": "string"
+                },
+                "nakshatraLord": {
+                  "type": "string"
+                },
+                "sign": {
+                  "type": "string"
+                },
+                "signLord": {
+                  "type": "string"
+                },
+                "subSublord": {
+                  "type": "string"
+                },
+                "sublord": {
+                  "type": "string"
+                }
+              },
+              "required": [
+                "longitude",
+                "degreeInSign",
+                "sign",
+                "signLord",
+                "nakshatra",
+                "nakshatraLord",
+                "sublord",
+                "subSublord",
+                "kpNumber",
+                "isRetrograde"
+              ],
+              "type": "object"
+            },
+            "type": "object"
+          },
+          "time": {
+            "type": "string"
+          }
+        },
+        "required": [
+          "date",
+          "time",
+          "datetime",
+          "planets"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "startDatetime": {
+      "type": "string"
+    },
+    "totalIntervals": {
+      "type": "number"
+    }
+  },
+  "required": [
+    "startDatetime",
+    "endDatetime",
+    "intervalMinutes",
+    "totalIntervals",
+    "ayanamsa",
+    "ayanamsaValue",
+    "intervals"
+  ],
+  "type": "object"
+}

Changed2 schema fields changedAug 17, 2026

addedInput schema / examples

Added value: +[
+  {
+    "endDatetime": "2025-01-15T23:59:00Z",
+    "intervalMinutes": 60,
+    "latitude": 28.6139,
+    "longitude": 77.209,
+    "startDatetime": "2025-01-15T00:00:00Z"
+  }
+]

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 10, 2026

changedInput schema / properties / nodeType / description

Previous value: -"Lunar node type for Rahu and Ketu positions. \"mean\" uses the smooth mean node (traditional Vedic astrology default). \"true\" uses the osculating node with perturbation corrections, oscillating up to 1.5 degrees from mean with a 173-day period. Impacts KP sub-lord assignments in narrow boundary cases. Defaults to \"mean\"."New value: +"Lunar node convention. \"mean\" is the smoothed average node, which always moves retrograde; \"true\" is the osculating node, which tracks the real perturbed node, oscillates up to about 1.5 degrees either side of the mean on a 173-day cycle, and can briefly turn direct. Neither is more correct and they almost always fall in the same sign. Applies to the Rahu and Ketu positions. Mean is the traditional Vedic default and what printed panchangs use; the choice can move a KP sub-lord in narrow boundary cases, where a span can be as small as 0.5 degrees. Defaults to \"mean\"."

Changed2 schema fields changedAug 1, 2026

changedInput schema / properties / ayanamsa / description

Previous value: -"Ayanamsa system for sidereal conversion. \"kp-newcomb\" uses the KP-Newcomb dynamic formula, the most common choice for KP astrology. \"kp-old\" uses the Krishnamurti original table from KP Reader-1 with constant precession rate. \"lahiri\" uses Lahiri/Chitrapaksha ayanamsa, matching most traditional Vedic software. Defaults to \"kp-newcomb\"."New value: +"Ayanamsa system for sidereal conversion. \"kp-newcomb\" uses the KP-Newcomb dynamic formula, the most common choice for KP astrology. \"kp-old\" uses the Krishnamurti original table from KP Reader-1 with constant precession rate. \"lahiri\" uses Lahiri/Chitrapaksha ayanamsa, matching most traditional Vedic software. \"raman\" uses the B.V. Raman ayanamsa from Hindu Predictive Astrology, a recognised traditional school that sits about 1.45 degrees below Lahiri. Defaults to \"kp-newcomb\"."

changedInput schema / properties / ayanamsa / enum

Previous value: -[
-  "kp-newcomb",
-  "kp-old",
-  "lahiri"
-]New value: +[
+  "kp-newcomb",
+  "kp-old",
+  "lahiri",
+  "raman"
+]

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"
+}

Changed2 schema fields changedJul 12, 2026

changedInput schema / properties / timezone / anyOf

Previous value: -[
-  {
-    "maximum": 14,
-    "minimum": -14,
-    "type": "number"
-  },
-  {
-    "pattern": "^[A-Za-z_]+(?:\\/[A-Za-z0-9_+-]+){0,2}$",
-    "type": "string"
-  }
-]New value: +[
+  {
+    "maximum": 14,
+    "minimum": -14,
+    "type": "number"
+  },
+  {
+    "type": "string"
+  }
+]

changedInput schema / properties / timezone / description

Previous value: -"Decimal hours from UTC OR IANA name (e.g. \"Asia/Kolkata\"). IANA resolved to the DST-correct offset for the startDatetime date. When non-zero, all datetimes are treated as local time in this timezone (Z suffix is ignored). Defaults to 0 (UTC)."New value: +"IANA name (e.g. \"America/New_York\", \"Europe/London\") OR decimal hours from UTC. IANA resolved to the DST-correct offset for the startDatetime date. When non-zero, all datetimes are treated as local time in this timezone (Z suffix is ignored). Defaults to 0 (UTC)."

First observedJul 8, 2026

TDQS

A4.2/5.0

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 safety profile is known. The description adds useful behavioral detail: returned fields, KP hierarchy, 7-day maximum range, and 15-minute to 24-hour intervals, which go beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is four purposeful sentences: what it does, what it returns, when to use it, and key constraints. There is no filler, and the most identifying information is front-loaded.

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?

Given the output schema, full parameter documentation, and annotations, the description is nearly complete. It covers purpose, return contents, use cases, and constraints, though it could have explicitly pointed users to single-time kp_planets or warned about large result sizes at dense intervals.

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 schema already documents all parameters thoroughly. The description adds context by mentioning the 7-day limit and interval granularity, but it does not need to compensate for undocumented parameters, keeping this at baseline.

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 a specific verb, resource, and scope: 'Calculate positions of all 9 planets... at regular time intervals' with the full KP hierarchy. This distinguishes it from single-timestamp siblings like kp_planets and from other interval-based tools that focus on ruling planets or cusps.

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 provides concrete use cases: tracking planetary motion, finding muhurta windows, analyzing transit patterns, and building ephemeris tables. It does not explicitly state when not to use it or name alternatives like single-point kp_planets, but the context is clear enough for correct selection.

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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