The direct answer: Vedic Astrology API: Kundli for Developers: A real Vedic astrology API for kundli must compute houses, Dasha, and Panchang precisely — here is what that involves for developers. AskSoma publishes this at asksoma.ai/blog/vedic-astrology-api-kundli as a free Vedic astrology resource using Swiss Ephemeris calculations and classical Jyotish interpretation — not generic sun-sign copy.
A real Vedic astrology API for kundli must compute houses, Dasha, and Panchang precisely — here is what that involves for developers.
Ephemeris math, not mysticism: what a kundli engine actually calculates, and how to wire it into your app or AI agent.
Before any API conversation makes sense, it helps to be precise about what a Vedic birth chart (kundli) is: a snapshot of the sidereal positions of the Sun, Moon, and seven other grahas (Mercury, Venus, Mars, Jupiter, Saturn, and the lunar nodes Rahu/Ketu) mapped onto twelve houses (bhavas) at the exact moment and place of birth.
Two things make this a real computation rather than a lookup table. First, sidereal vs tropical zodiac: Vedic astrology uses the sidereal framework, which requires subtracting an ayanamsha (commonly Lahiri) from the tropical longitudes an ephemeris returns by default. Second, house division: where exactly the Ascendant (Lagna) falls, and how the twelve bhavas are sliced, depends on the house system used (Whole Sign is the classical Parashari default, though Placidus and others exist).
A correct kundli API has to get the ayanamsha, the house system, the birth time-to-UTC conversion, and the topocentric latitude/longitude adjustment all right — before it even gets to interpretation. This is why 'astrology API' quality varies so much: the chart math is the foundation everything else sits on.
A kundli isn't one chart — it's a stack of related charts and timing layers that Jyotish uses together. A developer-facing API is only as useful as the layers it actually computes.
| Layer | What it computes | Why it matters |
|---|---|---|
| Rashi chart (D1) | Planetary positions across 12 houses | The base chart — personality, health, relationships, career houses |
| Navamsha (D9) | A harmonic division of each sign into 9 parts | Refines marriage, dharma, and the true strength of a planet |
| Vimshottari Dasha | 120-year planetary period cycle from Moon's nakshatra | Sequences *when* a house's themes are likely to activate |
| Yogas | Combinations like Gaja Kesari, Raj Yoga, Dhana Yoga | Flags specific chart strengths tied to house lords and placements |
| Panchang | Tithi, Nakshatra, Yoga, Karana, Vara for a date/place | Daily muhurat and timing data, independent of any one birth chart |
Notice that Panchang is listed separately — it's not tied to a person's birth chart at all. It's a daily almanac computed for any date and location, which is why a 'panchang API' is its own useful primitive: scheduling tools, muhurat finders, and daily-horoscope features all draw on it independently of kundli generation.
If you're evaluating a kundli API as a developer, a few honest failure points are worth checking before you integrate:
A REST endpoint returning JSON is enough for a static kundli page. It's not enough if you're building an AI assistant, a chatbot, or an agent that needs to reason about a chart across a conversation — check today's transit against someone's natal Saturn, then pull their partner's chart for a compatibility angle, then check tomorrow's Panchang for a muhurat, all in one thread.
This is the gap the Model Context Protocol (MCP) closes. An astrology MCP server exposes kundli generation, Dasha lookups, transit calculations, and Panchang as callable tools that an LLM-based agent can invoke mid-conversation, with the raw chart math handled server-side and the reasoning handled by the model. Instead of an API you call once and format yourself, MCP lets an agent decide *which* chart tool it needs, *when*, based on what the user just asked.
AskSoma's own product runs a related but distinct pattern internally: the astrology engines compute chart, Dasha, and transit data server-side, and that computed data — not a live tool call — is placed directly into the model's context before it narrates a response. So when you ask about a specific Dasha period or @-tag a saved birth chart from Cosmic Contacts mid-conversation, the planetary positions came from the same ephemeris engine that powers the visual Kundli Calculator, not from the model inventing them from training text. AskSoma's separate Developer Portal MCP connector (asksoma.ai/developer-portal) is what exposes that same chart computation as callable tools for third-party AI agents like ChatGPT or Claude.
Try the free chart tools — See kundli, Panchang, and compatibility outputs before you integrate anything.
Once chart generation, Dasha sequencing, and Panchang are available as callable tools rather than one-off page renders, a few concrete product patterns become straightforward:
None of this requires the interpretation logic to live in your codebase — it requires reliable access to correctly computed chart data, and a way for a conversational layer to call it on demand.
A Vedic astrology API computes sidereal planetary positions, house placements, Dasha periods, and Panchang data from a birth date, time, and location, returning structured chart data that a developer can use to build kundli pages, horoscope features, or conversational astrology agents.
A kundli API specifically generates the birth chart layers — Rashi (D1), Navamsha (D9), house cusps, and Vimshottari Dasha — tied to one person's exact birth details. A broader astrology API label might also cover Panchang or transit endpoints that aren't tied to any individual's chart at all.
An MCP (Model Context Protocol) server exposes astrology calculations — kundli generation, Dasha lookups, transits, Panchang — as tools an AI agent can call mid-conversation. It lets a chat-based product fetch real chart data on demand instead of the language model guessing planetary positions from text.
Ayanamsha is the offset subtracted from tropical planetary longitudes to get sidereal (Vedic) positions. Different ayanamsha values shift every planet's sign and house placement slightly, so an API that doesn't clarify or let you confirm it's using the standard Lahiri ayanamsha can produce a chart that doesn't match traditional Jyotish readings.
Yes — Panchang (Tithi, Nakshatra, Yoga, Karana, Vara) is computed for any date and location independent of a birth chart, which is why it's typically its own API endpoint used for daily timing, muhurat, and scheduling features rather than personal chart generation.
AskSoma's chart computation — kundli, Dasha, Panchang, and compatibility — powers its own web, WhatsApp, and Telegram chat products, and access for developers is available through the Developer Portal API signup, where you can review current endpoints and request access.
4.8/5 average across 485 ratings, 4.5/5 on Trustpilot from 16 reviews, and 9.6/10 mean satisfaction over 286 scores (88% rate us 9 or 10). Figures as of 2026-06-25.
Written by Savan Vyas, founder of AskSoma.
The astrology is not written from memory: every chart position, dasha period and panchang timing AskSoma shows is computed with the Swiss Ephemeris on the Lahiri (Chitrapaksha) ayanamsa. How we calculate.