AstrologyAPI.com vs Vedika: a developer-first comparison

If you are choosing between AstrologyAPI.com and Vedika for a horoscope, kundli, or matchmaking feature, the short answer is this: AstrologyAPI.com is a mature, REST-style catalog of computation endpoints, while Vedika pairs a comparable computation layer with a natural-language AI query endpoint, its own open-source ephemeris, and an MCP server for LLM agents. This guide compares them on coverage, request shapes, pricing, and the integration patterns that actually matter when you ship.

What each API is built for

Both services solve the same core problem — turn a birth date, time, and place into astrological data — but they optimize for different developer workflows.

AstrologyAPI.com

AstrologyAPI.com offers a large set of endpoints for Vedic horoscope, kundli, matchmaking, numerology, and Western reports, accessed with Basic Auth credentials. It is a well-established option with documentation organized around individual report endpoints, and many teams have shipped on it for years. Its strength is breadth of pre-formatted report endpoints, including ready-to-render prediction text in several languages.

Vedika

Vedika exposes 700+ API operations across 25 domains (704 enumerated as of June 2026) and adds two things on top of raw computation: a single natural-language endpoint that returns a written, source-grounded answer, and a streaming variant for chat-style UIs. It runs on the XALEN Ephemeris, Vedika's own open-source astronomical engine, and ships a public Model Context Protocol (MCP) server so LLM agents can call astrology tools directly.

Coverage and astrological systems

Where the two diverge most is in how many distinct astrological systems live behind one key.

Vedika carries Vedic, Western, and KP in a single API, with Jaimini, Tajaka, Lal Kitab, and numerology alongside them. If your product needs only Vedic report text in one or two languages, AstrologyAPI.com's catalog may already cover you. If you need to switch systems per user or expose a chat assistant, the single-key multi-system design reduces integration surface.

Request shapes side by side

AstrologyAPI.com endpoints typically accept day, month, year, hour, minute, latitude, longitude, and a timezone offset, authenticated with a user id and key over Basic Auth. Vedika splits its surface into a computation tier and an AI tier.

Vedika: natural-language query

The flagship endpoint takes a question plus structured birth details and returns a written answer:

curl -X POST https://api.vedika.io/api/v1/astrology/query \
  -H "x-api-key: vk_live_your_key" \
  -H "Content-Type: application/json" \
  -d '{
    "question": "When is a favourable window for changing jobs?",
    "birthDetails": {
      "datetime": "1990-05-14T08:30:00",
      "latitude": 18.5204,
      "longitude": 73.8567,
      "timezone": "Asia/Kolkata"
    },
    "speed": "fast"
  }'

Drop the speed field for the standard reasoning path; set it to "fast" for lower latency. For chat interfaces, post the same body to /api/v1/astrology/query/stream and read Server-Sent Events.

Vedika: V2 computation

If you only want structured chart data — planetary longitudes, houses, dashas — the V2 endpoints take flat fields and return JSON you render yourself:

import requests

resp = requests.post(
    "https://api.vedika.io/v2/astrology/birth-chart",
    headers={"x-api-key": "vk_live_your_key"},
    json={
        "datetime": "1990-05-14T08:30:00",
        "latitude": 18.5204,
        "longitude": 73.8567,
        "timezone": "Asia/Kolkata",
    },
)
chart = resp.json()
print(chart["ascendant"], chart["planets"])

This separation is useful in practice: the AI endpoint is for written guidance, the V2 endpoints are for charts and tables you control. With a report-catalog API like AstrologyAPI.com, you select the report endpoint that matches the output you want and render its returned text or fields.

The XALEN Ephemeris difference

Vedika computes positions with the XALEN Ephemeris, its own open-source engine released under Apache-2.0 and published to crates.io (xalen), PyPI (xalen), and npm (@xalen/wasm). It carries roughly 2,200 tests and was validated against JPL DE440 and the reference swetest tool, with zero charts deviating beyond 0.1° across a reproducible JPL DE440 benchmark sweep.

This is ephemeris precision — how closely computed planetary positions match astronomical reference data — not a claim about interpretive correctness, and it is not an endorsement by any space agency. The practical benefit is that you can audit the math: the engine is open source, so you can run the same calculations locally, pin a version, and verify outputs in your own CI. Most hosted astrology APIs, including AstrologyAPI.com, do not expose their calculation core for independent inspection, which is a reasonable trade-off if you prefer a fully managed black box.

AI agents and the MCP server

If you are building an assistant where an LLM agent should answer astrology questions, the integration model differs sharply. With a report-catalog API you write glue code: the model picks an endpoint, your backend formats the request, calls it, and feeds the result back. Vedika ships a public astrology MCP server so an MCP-compatible client or IDE can discover and call 21 astrology tools directly.

npx @vedika-io/mcp-server

Point any function-calling model or MCP-compatible client at it and the chart, dasha, compatibility, and panchang tools become callable without per-endpoint wiring. For teams putting an astrology feature behind a conversational interface, this removes a layer of orchestration code. AstrologyAPI.com remains a solid fit when you want deterministic report output rendered by your own UI rather than agent-driven calls.

Citations and source grounding

Vedika's written answers are constrained to attributable classical sources used in formal Jyotish, KP, and Western training — among them Brihat Parashara Hora Shastra, Phaladeepika, Saravali, Jataka Parijata, the Jaimini Sutras, Krishnamurti's KP Readers, and Ptolemy's Tetrabiblos. The intent is that an astrological statement traces to a real text rather than a paraphrase. If your product serves users who expect a citable basis, or if you operate in a context where defensible sourcing matters, this grounding is a meaningful differentiator. Report-catalog APIs generally return prediction text without a per-claim source trail, which is simpler to consume but harder to defend line by line.

Pricing

AstrologyAPI.com publishes paid plans around the $29/month range for its developer tier, with higher tiers for volume. Vedika prices by subscription with usage drawn from a wallet:

• Starter — $12/month
• Professional — $60/month
• Business — $120/month (adds the fast path and voice)
• Enterprise — $240/month

Per-query cost runs roughly $0.01–$0.05 depending on the path. A free sandbox requires no key, so you can validate request and response shapes before committing. For broader context, see how Vedika compares with other vendors such as Prokerala (around $19) and RoxyAPI (around $39) on the pricing page. Compare the actual cost per call against your expected query mix — a low monthly floor with per-call pricing behaves differently from a flat report-bundle plan at scale.

Key facts

• Vedika exposes 700+ operations across 25 domains (704 enumerated, June 2026); AstrologyAPI.com offers a mature catalog of report endpoints.
• Vedika's AI endpoint is POST /api/v1/astrology/query; structured charts come from /v2/astrology/*. Auth is x-api-key: vk_live_*.
• Vedic, Western, and KP run under one Vedika key, plus Jaimini, Tajaka, Lal Kitab, and numerology.
• The XALEN Ephemeris is open source (Apache-2.0), validated against JPL DE440 and swetest with zero charts beyond 0.1° across a 5M-chart test.
• Vedika ships a public MCP server (npx @vedika-io/mcp-server, 36 tools) and supports 30 languages.
• Vedika pricing: Starter $12, Professional $60, Business $120, Enterprise $240; per-query $0.01–$0.05; free sandbox.

Which one should you pick?

Choose AstrologyAPI.com if you want a straightforward catalog of pre-formatted report endpoints, are comfortable with Basic Auth, and your needs map cleanly onto its existing report list. Choose Vedika if you need multiple astrological systems behind one key, a natural-language or streaming AI answer endpoint, an auditable open-source ephemeris, source-grounded interpretations, or native LLM-agent integration through MCP. The cheapest reliable way to decide is to run your own birth-data fixtures through both: start with the Vedika sandbox, read the docs, and if you are migrating from another vendor, the migration walkthrough shows the request-mapping pattern.