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Vedic Astrology and Kundli MCP Server by RoxyAPI

Get Ashtakavarga (planetary strength) analysis - Ashtakavarga Calculator API

post_vedic_astrology_ashtakavarga
Read-only

Calculate complete Ashtakavarga analysis per Brihat Parashara Hora Shastra (BPHS). Returns Bhinnashtakavarga (BAV), Sarvashtakavarga (SAV, total 337), Reduced Ashtakavarga (Trikona + Ekadipati Shodhana per Ch. 67-68), and Shodhya Pinda planetary strength (Rashi Pinda + Graha Pinda per Ch. 69). Essential for transit prediction timing, house strength analysis, dasha result evaluation, and planetary strength comparison. Ashtakavarga calculator API, bindu rekha points, Shodhya Pinda, Vedic astrology.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYesBirth 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).
timeYesBirth 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.
compactNoSet 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.
ayanamsaNoSidereal 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
latitudeYesBirth 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.
timezoneNoTimezone: 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.
longitudeYesBirth location longitude in decimal degrees. Affects local time calculations and ayanamsha adjustments. Example: Delhi 77.2090, Mumbai 72.8777, Kathmandu 85.3240.
ayanamsaValueNoCustom 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
NameRequiredDescriptionDefault
frameYes
signsYes
shodhyaPindaYes
sarvashtakavargaYes
bhinnashtakavargaYes
reducedSarvashtakavargaYes
reducedBhinnashtakavargaYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • 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."
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "properties": {
      +    "bhinnashtakavarga": {
      +      "items": {
      +        "properties": {
      +          "bindus": {
      +            "items": {
      +              "type": "number"
      +            },
      +            "type": "array"
      +          },
      +          "planet": {
      +            "type": "string"
      +          },
      +          "total": {
      +            "type": "number"
      +          }
      +        },
      +        "required": [
      +          "planet",
      +          "bindus",
      +          "total"
      +        ],
      +        "type": "object"
      +      },
      +      "type": "array"
      +    },
      +    "frame": {
      +      "properties": {
      +        "ayanamsa": {
      +          "type": "string"
      +        },
      +        "ayanamsaDegrees": {
      +          "type": "number"
      +        }
      +      },
      +      "required": [
      +        "ayanamsa",
      +        "ayanamsaDegrees"
      +      ],
      +      "type": "object"
      +    },
      +    "reducedBhinnashtakavarga": {
      +      "items": {
      +        "properties": {
      +          "bindus": {
      +            "items": {
      +              "type": "number"
      +            },
      +            "type": "array"
      +          },
      +          "planet": {
      +            "type": "string"
      +          },
      +          "total": {
      +            "type": "number"
      +          }
      +        },
      +        "required": [
      +          "planet",
      +          "bindus",
      +          "total"
      +        ],
      +        "type": "object"
      +      },
      +      "type": "array"
      +    },
      +    "reducedSarvashtakavarga": {
      +      "properties": {
      +        "bindus": {
      +          "items": {
      +            "type": "number"
      +          },
      +          "type": "array"
      +        },
      +        "total": {
      +          "type": "number"
      +        }
      +      },
      +      "required": [
      +        "bindus",
      +        "total"
      +      ],
      +      "type": "object"
      +    },
      +    "sarvashtakavarga": {
      +      "properties": {
      +        "bindus": {
      +          "items": {
      +            "type": "number"
      +          },
      +          "type": "array"
      +        },
      +        "total": {
      +          "type": "number"
      +        }
      +      },
      +      "required": [
      +        "bindus",
      +        "total"
      +      ],
      +      "type": "object"
      +    },
      +    "shodhyaPinda": {
      +      "items": {
      +        "properties": {
      +          "grahaPinda": {
      +            "type": "number"
      +          },
      +          "planet": {
      +            "type": "string"
      +          },
      +          "rashiPinda": {
      +            "type": "number"
      +          },
      +          "shodhyaPinda": {
      +            "type": "number"
      +          }
      +        },
      +        "required": [
      +          "planet",
      +          "rashiPinda",
      +          "grahaPinda",
      +          "shodhyaPinda"
      +        ],
      +        "type": "object"
      +      },
      +      "type": "array"
      +    },
      +    "signs": {
      +      "items": {
      +        "enum": [
      +          "Aries",
      +          "Taurus",
      +          "Gemini",
      +          "Cancer",
      +          "Leo",
      +          "Virgo",
      +          "Libra",
      +          "Scorpio",
      +          "Sagittarius",
      +          "Capricorn",
      +          "Aquarius",
      +          "Pisces"
      +        ],
      +        "type": "string"
      +      },
      +      "type": "array"
      +    }
      +  },
      +  "required": [
      +    "frame",
      +    "bhinnashtakavarga",
      +    "sarvashtakavarga",
      +    "reducedBhinnashtakavarga",
      +    "reducedSarvashtakavarga",
      +    "shodhyaPinda",
      +    "signs"
      +  ],
      +  "type": "object"
      +}
  3. Changed1 schema field changed
    • 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."
  4. Changed2 schema fields changed
    • 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."
  5. Changed2 schema fields changed
    • 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"
      +}
  6. Changed1 schema field changed
    • 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."
  7. Changed1 schema field changed
    • 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"
      +}
  8. Changed2 schema fields changed
    • 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."
  9. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds what analysis is performed and the specific components returned, which is useful. But it does not disclose edge cases, limitations, or any behavioral caveats (e.g., dependencies on ayanamsa precision), leaving some burden uncovered. With annotations present, the additional value is modest but non-trivial.

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

Conciseness3/5

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

The first two sentences are dense and informative, front-loading the core action and outputs. However, the final sentence ('Ashtakavarga calculator API, bindu rekha points, Shodhya Pinda, Vedic astrology.') is keyword stuffing that earns no place for an agent selecting or calling the tool. This noise pulls the structure score down from a clean 4.

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 existence of a detailed output schema and 100% documented parameters, the description covers the essential context: what is calculated, the authoritative source (BPHS), the exact components, and the use cases. It could add guidance on when Ashtakavarga is preferred over shadbala, but that is a minor gap. For a complex astrological tool, the description is adequately complete.

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% (all 8 parameters are fully described inline), so the baseline is 3. The tool description does not add any parameter-specific semantic information; it only mentions domain concepts like 'bindu rekha points' that do not map to specific parameters. Thus it neither improves nor harms the schema's already thorough parameter documentation.

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, actionable verb-resource pair: 'Calculate complete Ashtakavarga analysis per Brihat Parashara Hora Shastra (BPHS).' It names concrete outputs (Bhinnashtakavarga, Sarvashtakavarga, Reduced Ashtakavarga, Shodhya Pinda) that distinguish it from every sibling tool, none of which mention Ashtakavarga. An agent can reliably tell what this tool does 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 Guidelines4/5

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

The description provides clear application context: 'Essential for transit prediction timing, house strength analysis, dasha result evaluation, and planetary strength comparison.' This tells an agent when to reach for this tool. However, it does not name sibling alternatives (e.g., post_vedic_astrology_shadbala) or state explicit exclusion conditions, so it stops short of full when-not guidance.

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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