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
AI Astrology API: One Endpoint, a Grounded Reading — Not Raw JSON
A calculation API hands you JSON and leaves the interpretation to you. 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. Astrological facts are computed by code first and then interpreted, and the chart used comes back in the response so you can check the reading against it.
Keyless sandbox (mock data, no API key) · open-source engine you can pip install · transparent public pricing from $12/mo. Part of the Vedika astrology API; for chart-data routes see the astrology API endpoint and coverage reference.
What "AI-native" actually means here
Vedika is built around the computed chart: a deterministic astrology engine computes it, and an astrology-specialized LLM reasons over those computed numbers. Three things make that concrete.
AI-native
Grounded, not guessed
Planetary positions, yogas, doshas and dashas are computed by the engine rather than generated by the model. The AI interprets that computed data and is source-grounded to classical texts (BPHS, Phaladeepika, Saravali, Jaimini). The chart used comes back in the response.
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 48 tools natively. A first-party MCP server.
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": "<computed from birth details>",
"seventhHouseLord": "<computed>",
"activeDasha": "<computed Vimshottari period>"
},
"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.
What a response looks like
Sample responses, drawn with the same widgets you can embed on your own site.
Response examples for every endpoint are in the API reference.
An open-source engine you can inspect yourself
The calculation core is XALEN Ephemeris — Apache-2.0, published openly, with a test suite and a validation suite you can run 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 a test suite you can run yourself. Try the engine locally, no account needed:
pip install xalenOpen source
A validation suite you can run
The repository includes a validation suite for the engine. Run it yourself:
cargo run -p xalen-validationThe source and the suite are published openly, so you can read exactly what is checked.
Depth and breadth, in the same API
1,138
API operations across 12 systems — Vedic, Western/tropical, KP, Vastu, Tarot, BaZi, Numerology, Jaimini, Tajaka, Lal Kitab, Human Design, Matrimony, Prashna and more.
30
Language codes accepted; coverage differs by endpoint. Spoken Voice AI readings on Business and higher plans.
Vedic
Divisional charts, yogas, doshas and dashas — the depth 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
Starter through Enterprise are published with their prices. Production usage is billed per call from a wallet.
Starter
$12/mo
Professional
$60/mo
Business
$120/mo
Adds Voice AI + fast path
Enterprise
$240/mo
Larger needs
Custom
Beyond the published Enterprise plan — talk to us
There is a keyless sandbox with mock data for testing and an open-source engine to evaluate, but no free production tier.
When Vedika fits — and when it may not
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 want answers built from code-computed chart facts with 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 — a calculation-only API may suit you better.
- 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 try the request and response shape in the keyless 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?
Astrological facts such as planetary positions, yogas, doshas and dashas are computed by code in the engine, not generated by the model. The AI interprets that computed chart data and is grounded to classical texts (BPHS, Phaladeepika, Saravali, Jaimini). The chart used comes back in the response, so you can check a reading against it.
Can I inspect the calculation engine?
Yes. The calculation core, XALEN Ephemeris, is open source (Apache-2.0) on crates.io, npm and PyPI. You can run its tests and its validation suite yourself with cargo run -p xalen-validation.
Can AI agents use Vedika directly?
Yes. Run npx @vedika-io/mcp-server to expose a first-party MCP server with 48 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 keyless sandbox with mock data — no API key needed — for testing your integration, and you can try the open-source engine with pip install xalen. There is no free production tier: production is billed per call from a wallet, and plans start at $12/mo.
Which astrology systems and languages are supported?
1,138 API operations across 12 systems including Vedic, Western/tropical, KP, Vastu, Tarot, Chinese/BaZi, Numerology, Jaimini, Tajaka, Lal Kitab, Human Design, Matrimony and Prashna, including divisional charts, yogas, doshas and dashas. Responses come in any of 30 language codes. Voice AI readings are available on Business and higher plans.
See the grounded reading for yourself
Try the natural-language endpoint in the keyless sandbox (mock data, no API key), or read the integration guide. The engine is open source if you want to inspect it first.