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Vedic Astrology and Kundli MCP Server by RoxyAPI

by com.roxyapi

Check Kalsarpa Dosha - Kalsarpa Yoga Calculator API

post_vedic_astrology_dosha_kalsarpa
Read-only

Detect Kalsarpa dosha (Kalsarpa yoga) when all 7 planets are hemmed between Rahu-Ketu axis. Accurate kalsarpa dosha calculator identifying 12 types (Ananta, Kulik, Vasuki, Shankhapala, Padma, Mahapadma, Takshak, Karkotak, Shankhachud, Ghatak, Vishdhar, Sheshnag). Returns severity and effects based on Rahu house position. Essential for Vedic astrology dosha analysis, birth chart evaluation, and matrimonial compatibility. Considered significant dosha affecting life obstacles and spiritual growth.

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).
langNoResponse 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
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: 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.
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.

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 covered. The description adds behavioral detail beyond annotations by specifying the exact condition for detection, enumerating 12 Kalsarpa types, and stating that severity and effects depend on Rahu's house position.

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 front-loaded with the core detection logic and remains substantive without fluff. Each sentence adds value: the condition, the 12-type taxonomy, the returned severity/effects, and the use-case context.

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 tool's complexity and absence of an output schema, the description adequately covers the domain meaning, key return concepts (severity, effects, Rahu house), and common use cases. It does not fully describe the overall response structure, but the description and rich parameter schema together give an agent sufficient grounding to invoke it correctly.

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 documents all 9 parameters with detailed meanings, defaults, and formats. The description itself adds no parameter-specific guidance, which matches the baseline for high schema coverage.

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 uses a specific verb ('Detect') with a clear resource ('Kalsarpa dosha') and defines the astronomical condition (all 7 planets hemmed between Rahu-Ketu axis). It differentiates this from sibling dosha tools like dosha_manglik or dosha_sadhesati by naming the specific dosha and the 12 sub-types.

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 states the practical contexts where the tool matters: dosha analysis, birth chart evaluation, and matrimonial compatibility. It does not explicitly name alternatives or exclusion conditions, but the purpose and scope are clear enough that an agent can infer this is the tool for Kalsarpa-specific checks rather than other doshas.

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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TDQS

A3.6/5.0
Disambiguation3/5

Many tools have overlapping concepts (multiple dasha levels, monthly variants, aspects, transit), but detailed descriptions clarify each one's distinct purpose. Still, a few pairs like planetary_positions vs birth_chart or aspects_monthly vs aspects_lunar could confuse an agent initially.

Naming Consistency5/5

All tools follow a strict get_vedic_astrology_* or post_vedic_astrology_* prefix with snake_case resource names. The pattern is predictable and uniformly applied, including the hierarchical dasha drill-downs, making it easy to infer tool families.

Tool Count1/5

With 50 tools, the server is extremely heavy. Many are monthly, interval, or sub-level variants that could be parameterized or consolidated, making the set feel bloated and difficult to navigate for an agent.

Completeness5/5

The tool set covers nearly the entire Vedic astrology domain: reference data (nakshatras, rashis, yoga glossary), core charts (birth, navamsa, divisional), dasha hierarchy, transits, compatibility, doshas, panchang, KP system, and advanced calculations like Shadbala and Ashtakavarga. No significant gaps are apparent.

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