AI-native
One natural-language endpoint
POST /api/v1/astrology/query takes a plain-English question and birth details and returns a grounded, conversational reading — not JSON you have to translate into prose yourself.
AI-Native Astrology API
The Best AI Astrology API: One Endpoint, a Grounded Reading — Not Raw JSON
Most astrology APIs hand you calculation JSON and leave you to interpret it. Vedika ships a built-in astrology LLM: send a free-text question plus birth details to one endpoint and get back a conversational, source-grounded reading. Every astrological fact is code-computed first, then interpreted — so it doesn't hallucinate degrees and houses the way a general-purpose chatbot does.
Free keyless sandbox (mock endpoints, no signup) · open-source engine you can pip install · transparent public pricing from $12/mo.
What "AI-native" actually means here
Plenty of providers add a chatbot wrapper. Vedika is built the other way around: a deterministic astrology engine computes the chart, and an astrology-specialized LLM reasons over those verified numbers. Three things make that real rather than marketing.
AI-native
Grounded, not guessed
Planetary positions, yogas, doshas and dashas are computed by the engine — never model-guessed. The AI only interprets verified data and is source-grounded to classical texts (BPHS, Phaladeepika, Saravali, Jaimini).
AI-native
Native MCP for AI agents
Run npx @vedika-io/mcp-server and any MCP-compatible AI assistant or IDE can call Vedika's 36 tools natively. A first-party MCP server, not a community shim.
The natural-language call, in one request
Ask a question the way a person would. The engine resolves the chart, then returns a reading grounded in the computed facts.
curl -X POST https://api.vedika.io/api/v1/astrology/query \
-H "Authorization: Bearer vk_live_your_key" \
-H "Content-Type: application/json" \
-d '{
"question": "When is a good period for marriage, and what should I watch for?",
"birthDetails": {
"datetime": "1992-08-17T14:30:00",
"latitude": 18.5204,
"longitude": 73.8567,
"timezone": "Asia/Kolkata"
}
}'What comes back — a grounded reading, not raw coordinates:
{
"success": true,
"response": "Marriage timing is read from your 7th house, its lord, and
the running dasha period. The reading below is built from your computed
chart — the 7th-house lord's strength and placement, Venus's condition
(the natural significator of marriage), and which Mahadasha/Antardasha is
active over the years you asked about — then interpreted in plain language
with the supportive and cautionary windows called out...",
"birthChart": {
"ascendant": "",
"seventhHouseLord": "",
"activeDasha": ""
},
"metadata": { "grounding": "classical-text", "engine": "XALEN Ephemeris" }
} The birthChart block is deterministic engine output; the response is the AI's interpretation of exactly those computed facts, grounded in the classical-text method (not a generic chatbot guess).
An open-source engine you can verify yourself
Accuracy claims are cheap. Ours are runnable. The calculation core is XALEN Ephemeris — Apache-2.0, published openly, validated against NASA JPL DE440, and reproducible on your own machine.
Open source
Published and installable
XALEN Ephemeris is on crates.io (15 crates), npm (@xalen/wasm) and PyPI (xalen) under Apache-2.0, with 2,200+ tests. Try the engine for free, no account:
pip install xalenOpen source
A reproducible benchmark
Validated against JPL DE440 with sub-arcsecond mean agreement on the planets (analytic Moon ~2.2 arcsec) over a 3,653-epoch-per-body grid. Run it yourself:
cargo run -p xalen-validationFull results published at vedika.io/benchmarks. We match the reference standard — we don't claim to beat it.
Depth and breadth, in the same API
704
API operations across 25 systems — Vedic, Western/tropical, KP, Vastu, Tarot, BaZi, Numerology, Jaimini, Tajaka, Lal Kitab, Human Design, Matrimony, Prashna and more.
14
Languages for spoken Voice AI readings (speech in → reading → speech out) on Business and higher plans. 30 languages platform-wide, 14 of them Indic.
60
Divisional charts and 300+ yoga detections — the granular Vedic depth serious astrology products need.
36
Native MCP tools so AI agents can call Vedika directly, plus SDKs for JS, Python, React and Flutter.
Transparent, public pricing
No "contact sales to see a number." Every plan is published, and the AI-native entry point is the lowest among the providers we compare against.
Starter
$12/mo
Professional
$60/mo
Business
$120/mo
Adds Voice AI + fast path
Enterprise
$240/mo
Dedicated
$1,999/mo
For comparison, Prokerala starts at $19/mo and AstrologyAPI at $29/mo — both solid calculation APIs, but neither ships the AI-native reasoning layer. There is a free keyless sandbox for testing and a free open-source engine to evaluate, but no free production tier.
When Vedika is the right AI astrology API — and when another may fit
Choose Vedika when…
- You want grounded natural-language readings, not JSON you have to render into prose.
- You're building an AI agent or chatbot and want a first-party MCP server.
- You need anti-hallucination guarantees backed by code-computed facts and cited classical sources.
- You want to audit the calculation engine yourself — it's open source.
- You need voice readings or deep multi-system Vedic coverage.
Another API may fit when…
- You only need raw calculation JSON and will write all interpretation yourself — established providers like Prokerala and AstrologyAPI do this well.
- You already have your own astrology reasoning layer and just want positions and divisional data.
- Your use case is narrow enough that an AI reasoning layer adds cost you don't need.
Honest fit beats a forced sale — and you can validate everything above in the free sandbox before committing.
Frequently asked questions
What makes Vedika an "AI-native" astrology API?
A single endpoint, POST /api/v1/astrology/query, accepts a free-text question plus birth details and returns a grounded, conversational reading. You don't have to parse calculation JSON and write interpretation logic yourself — the built-in astrology LLM does the reasoning over verified computed data.
How does it avoid hallucinating astrological facts?
Every astrological fact — planetary positions, yogas, doshas, dashas — is code-computed by the engine, never model-guessed. The AI interprets only that verified data and is source-grounded to classical texts (BPHS, Phaladeepika, Saravali, Jaimini), so it doesn't invent degrees or houses the way a general chatbot would.
Can I verify the calculation accuracy?
Yes. The calculation core, XALEN Ephemeris, is open source (Apache-2.0) on crates.io, npm and PyPI with 2,200+ tests. It's validated against NASA JPL DE440 with sub-arcsecond mean agreement on the planets, and you can reproduce the benchmark yourself with cargo run -p xalen-validation. Results are published at vedika.io/benchmarks.
Can AI agents use Vedika directly?
Yes. Run npx @vedika-io/mcp-server to expose a first-party MCP server with 36 tools. Any MCP-compatible AI assistant or IDE can call Vedika natively without custom glue code.
Is there a free way to try it?
There's a free keyless sandbox with mock endpoints — no signup required — for testing integration. The calculation engine is also free to evaluate via the open-source package (pip install xalen). Note there is no free production tier; paid plans start at $12/mo.
Which astrology systems and languages are supported?
704 operations across 25 systems including Vedic, Western/tropical, KP, Vastu, Tarot, Chinese/BaZi, Numerology, Jaimini, Tajaka, Lal Kitab, Human Design, Matrimony and Prashna, with 60 divisional charts and 300+ yoga detections. The platform supports 30 languages (15 Indic), and Voice AI readings are available in 14 languages on Business and higher plans.
See the grounded reading for yourself
Try the natural-language endpoint in the free keyless sandbox, or read the integration guide. No signup needed to start — and the engine is open source if you want to verify it first.