Vedic Astrology and Kundli MCP Server by RoxyAPI

Detect classical Vedic yogas in a birth chart

post_vedic_astrology_yoga_detect

Read-only

Chart-driven detection of 48 classical Vedic yogas. Twelve conjunction and dignity yogas: Gajakesari (parashara three-rule definition), Sunapha, Anapha, Dhurdhura, Kemadruma, Chandra Mangala, Budha-Aditya, and the five Pancha Mahapurusha yogas (Ruchaka, Bhadra, Hamsa, Malavya, Sasa). Plus all 32 Nabhasa distribution yogas, which describe how the seven visible grahas are spread across the whole chart rather than any single conjunction, across four families: Asraya (Rajju, Musala, Nala), Dala (Mala, Sarpa), Akriti (Gada, Shakata, Vihaga, Shringataka, Hala, Vajra, Yava, Kamala, Vapi, Yupa, Shara, Shakti, Danda, Nauka, Kuta, Chhatra, Dhanusha, Ardhachandra, Chakra, Samudra) and Sankhya (Gola, Yuga, Shoola, Kedara, Pasa, Damini, Veena). Plus four wealth and poverty verdicts, each ONE answer over a whole family of classical rules: Dhana Yoga over the eleven catalogued wealth combinations of BPHS ch. 41, Daridra Yoga over the poverty combinations of BPHS ch. 42 and Phaladeepika ch. 6, Lakshmi Yoga (BPHS ch. 36), and Dhana Malika (Jataka Parijata ch. 7). Their evidence names every rule that matched and the exact condition it matched on, so a wealth reading cites the combination rather than a label, and a rule resting on a single authority is excluded from the verdict and says so rather than quietly counting. Each yoga is returned with an id, name, a present boolean, a quality (Positive, Negative, or Both, i.e. auspicious, inauspicious, or context-dependent), and a classical-text evidence string naming the rule that triggered or failed (kendra position, dignity, malefic drishti, lordship, retrograde state, sign modality, bhava distribution). Nabhasa results also apply the four classical precedence norms, so a yoga that matched its own rule but was outranked by a stronger family is returned as absent with evidence naming the norm that silenced it, letting you explain a verdict rather than only report it. There is no separate major/minor flag; quality is the auspiciousness axis. Unlike GET /yoga and GET /yoga/{id} which are dictionary lookups, this endpoint computes the kundli from birth data and runs the detection rules. Sources: BPHS ch. 35 and ch. 75, Mantreswara Phaladeepika ch. 6, B.V. Raman Three Hundred Important Combinations.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`date`	Yes	Birth date in YYYY-MM-DD format. Date determines planetary positions and nakshatra calculations for Vedic kundli (janam patri). Accurate birth date is essential for dashas, yoga calculations, and divisional charts (vargas).
`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
`time`	Yes	Birth time in 24-hour HH:MM:SS format. Time is CRITICAL for Lagna (Ascendant) calculation and house divisions. It changes every two hours roughly. Even minutes matter for accurate nakshatra pada and divisional chart (D9, D10) calculations. Without exact time, Lagna and house-based predictions will be incorrect.
`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	Sidereal frame (ayanamsa) the chart is cast in. "lahiri" is Lahiri/Chitrapaksha, the traditional Vedic standard used by most software, and is the default. "raman" is the B.V. Raman ayanamsa from Hindu Predictive Astrology, about 1.45 degrees below Lahiri. "kp-newcomb" and "kp-old" are the two Krishnamurti Paddhati frames. "custom" takes your own value in degrees via ayanamsaValue, for reconciling exactly against a specific reference program. The frame rotates the whole zodiac, so a graha sitting within 1.45 degrees of a boundary can change rashi or nakshatra when you switch: pick the one your reference software uses and keep it.	lahiri
`latitude`	Yes	Birth location latitude in decimal degrees. Location determines local sidereal time for Lagna calculation and affects bhava (house) cusps. Example: Delhi 28.6139, Mumbai 19.0760, Kathmandu 27.7172.
`timezone`	No	Timezone: an IANA name (e.g. "America/New_York", "Europe/London", or `cities[0].timezone` from /location/search) or decimal hours from UTC (e.g. -5 for EST, 5.5 for IST). An IANA name is resolved to the offset in force at the given date and time. Defaults to 5.5.
`longitude`	Yes	Birth location longitude in decimal degrees. Affects local time calculations and ayanamsha adjustments. Example: Delhi 77.2090, Mumbai 72.8777, Kathmandu 85.3240.
`ayanamsaValue`	No	Custom ayanamsa value in degrees. When provided, overrides the computed ayanamsa from the selected type. Use for testing with specific ayanamsa values or matching a particular reference source.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`frame`	Yes
`total`	Yes
`yogas`	Yes
`birthDetails`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 23, 2026

changedInput schema / properties / timezone / description

Previous value: -"Timezone: IANA name (e.g. \"America/New_York\", \"Europe/London\") OR decimal hours from UTC (e.g. -5 for EST, 1 for CET). IANA strings are resolved to the offset in force at the given date and time, so you can pass `cities[0].timezone` from /location/search directly. Defaults to 5.5."New value: +"Timezone: an IANA name (e.g. \"America/New_York\", \"Europe/London\", or `cities[0].timezone` from /location/search) or decimal hours from UTC (e.g. -5 for EST, 5.5 for IST). An IANA name is resolved to the offset in force at the given date and time. Defaults to 5.5."

Changed1 schema field changedSep 20, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "birthDetails": {
+      "properties": {
+        "date": {
+          "type": "string"
+        },
+        "latitude": {
+          "type": "number"
+        },
+        "longitude": {
+          "type": "number"
+        },
+        "time": {
+          "type": "string"
+        },
+        "timezone": {
+          "type": "number"
+        }
+      },
+      "required": [
+        "date",
+        "time",
+        "latitude",
+        "longitude",
+        "timezone"
+      ],
+      "type": "object"
+    },
+    "frame": {
+      "properties": {
+        "ayanamsa": {
+          "type": "string"
+        },
+        "ayanamsaDegrees": {
+          "type": "number"
+        }
+      },
+      "required": [
+        "ayanamsa",
+        "ayanamsaDegrees"
+      ],
+      "type": "object"
+    },
+    "total": {
+      "type": "number"
+    },
+    "yogas": {
+      "items": {
+        "properties": {
+          "description": {
+            "type": "string"
+          },
+          "evidence": {
+            "type": "string"
+          },
+          "family": {
+            "enum": [
+              "classical",
+              "asraya",
+              "dala",
+              "akriti",
+              "sankhya"
+            ],
+            "type": "string"
+          },
+          "id": {
+            "type": "string"
+          },
+          "name": {
+            "type": "string"
+          },
+          "present": {
+            "type": "boolean"
+          },
+          "quality": {
+            "enum": [
+              "Positive",
+              "Negative",
+              "Both"
+            ],
+            "type": "string"
+          },
+          "result": {
+            "type": "string"
+          },
+          "suppressedBy": {
+            "enum": [
+              "classical",
+              "asraya",
+              "dala",
+              "akriti",
+              "sankhya"
+            ],
+            "type": "string"
+          }
+        },
+        "required": [
+          "id",
+          "name",
+          "description",
+          "result",
+          "quality",
+          "family",
+          "present"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "yogas",
+    "frame",
+    "total",
+    "birthDetails"
+  ],
+  "type": "object"
+}

Changed1 schema field changedSep 16, 2026

changedInput schema / properties / timezone / description

Previous value: -"Timezone: IANA name (e.g. \"America/New_York\", \"Europe/London\") OR decimal hours from UTC (e.g. -5 for EST, 1 for CET). IANA strings are resolved to the DST-correct offset for the given date, so you can pass `cities[0].timezone` from /location/search directly. Defaults to 5.5."New value: +"Timezone: IANA name (e.g. \"America/New_York\", \"Europe/London\") OR decimal hours from UTC (e.g. -5 for EST, 1 for CET). IANA strings are resolved to the offset in force at the given date and time, so you can pass `cities[0].timezone` from /location/search directly. Defaults to 5.5."

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: +[
+  {
+    "date": "1990-07-04",
+    "latitude": 28.6139,
+    "longitude": 77.209,
+    "time": "10:12:00"
+  }
+]

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."

Changed2 schema fields changedAug 2, 2026

addedInput schema / properties / ayanamsa

Added value: +{
+  "default": "lahiri",
+  "description": "Sidereal frame (ayanamsa) the chart is cast in. \"lahiri\" is Lahiri/Chitrapaksha, the traditional Vedic standard used by most software, and is the default. \"raman\" is the B.V. Raman ayanamsa from Hindu Predictive Astrology, about 1.45 degrees below Lahiri. \"kp-newcomb\" and \"kp-old\" are the two Krishnamurti Paddhati frames. \"custom\" takes your own value in degrees via ayanamsaValue, for reconciling exactly against a specific reference program. The frame rotates the whole zodiac, so a graha sitting within 1.45 degrees of a boundary can change rashi or nakshatra when you switch: pick the one your reference software uses and keep it.",
+  "enum": [
+    "kp-newcomb",
+    "kp-old",
+    "lahiri",
+    "raman",
+    "custom"
+  ],
+  "example": "lahiri",
+  "type": "string"
+}

addedInput schema / properties / ayanamsaValue

Added value: +{
+  "description": "Custom ayanamsa value in degrees. When provided, overrides the computed ayanamsa from the selected type. Use for testing with specific ayanamsa values or matching a particular reference source.",
+  "example": 24,
+  "type": "number"
+}

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: -"Timezone: decimal hours from UTC (e.g. 5.5 for IST, -5 for EST) OR IANA name (e.g. \"Asia/Kolkata\", \"America/New_York\"). IANA strings are resolved to the DST-correct offset for the given date, so you can pass `cities[0].timezone` from /location/search directly. Defaults to 5.5 (IST)."New value: +"Timezone: IANA name (e.g. \"America/New_York\", \"Europe/London\") OR decimal hours from UTC (e.g. -5 for EST, 1 for CET). IANA strings are resolved to the DST-correct offset for the given date, so you can pass `cities[0].timezone` from /location/search directly. Defaults to 5.5."

First observedJul 8, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations only declare readOnlyHint=true and destructiveHint=false; the description far exceeds that by disclosing how evidence is produced, how Nabhasa precedence norms can silence a matched yoga, the absence/presence semantics, and the absence of a major/minor flag with quality as the auspiciousness axis. This gives the agent a clear behavioral model beyond the structured hints.

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 front-loaded with the core purpose and organized into clear thematic units (conjunction yogas, Nabhasa yogas, wealth verdicts, output behavior, alternatives). It loses a point for exhaustively listing every individual yoga name and family member, which is more detail than an agent needs to select or invoke the tool and makes the description heavier to scan.

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?

Given the tool's domain complexity, the description covers what is computed, the 48-yoga scope, output shape (id, name, present, quality, evidence), exception behavior (silenced yogas, single-authority exclusions), source texts, and the distinction from dictionary endpoints. No material invocation or interpretation information is missing.

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 input schema already fully documents date, time, latitude, longitude, timezone, ayanamsa, and the rest. The tool description adds no parameter-specific semantics beyond saying the endpoint computes from birth data, which is acceptable under the high-coverage 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 opens with a specific verb and resource: 'Chart-driven detection of 48 classical Vedic yogas.' It goes on to define exact scope, the output, and explicitly contrasts itself with GET /yoga and GET /yoga/{id} dictionary lookups, so an agent can distinguish it from sibling tools without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The final paragraph states the decision rule: unlike GET /yoga and GET /yoga/{id}, which are dictionary lookups, this endpoint computes the kundli from birth data and runs detection rules. That is an explicit condition and alternative, which is exactly what an agent needs to choose this tool.

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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