Vedika vs RoxyAPI 2026: In-House Calculations vs API Wrapper

A new entrant called RoxyAPI (roxyapi.com) appeared in late 2024 and has since published marketing materials positioning itself in the astrology API market. Their domain was registered in April 2024. They claim 86+ endpoints across six domains and advertise MCP (Model Context Protocol) support as a headline feature. Recently, RoxyAPI published a competitor comparison article that placed Vedika's pricing at $7,500 to $22,500 per month.

Vedika's actual pricing starts at $12 per month. That discrepancy — a factor of up to 94x — is a useful starting point for this comparison, because it forces a question every developer should ask before signing up for any API: what else on this page is fabricated?

This article examines both services on verifiable criteria: calculation methodology, feature depth, developer tooling, transparency, and pricing. We will be direct about where Vedika leads, where the comparison is genuinely uncertain, and what RoxyAPI's public record does and does not establish.

About the Two Products

Vedika

Vedika is a B2B API platform built by XALEN Technology, based in Pune, Maharashtra. The product launched in 2025, is built on Google Cloud Platform, and currently serves 1,500+ registered users with 18,446 real API transactions recorded. The team is named and reachable. Vedika runs 102 Vedic and 17 Western in-house calculators directly on Swiss Ephemeris — no external astrology API dependency. The backend is a TypeScript/Express service with two Cloud Run regions (US and Mumbai), Neon PostgreSQL for pgvector RAG, and a 6-layer anti-hallucination pipeline for AI responses.

Pricing is $12/month (Starter), $60/month (Pro), $120/month (Business), $240/month (Enterprise). All plans are documented on the public pricing page. There is no free tier but there is a free sandbox with 65 mock endpoints requiring no authentication.

RoxyAPI

RoxyAPI (roxyapi.com) is a newer service with a domain registered April 2024. They list 86+ endpoints organized across six domains. The site advertises MCP (Model Context Protocol) support as a primary differentiator. The founder and team are anonymous — no names, LinkedIn profiles, or company registration details are visible on the site. No pricing is published. No customer names, case studies, or usage statistics are provided. The site displays a 5.0/5.0 rating aggregated from 127 reviews; clicking into the rating shows no individual review text or reviewer names.

What RoxyAPI's calculation engine is — whether it performs in-house ephemeris calculations, proxies a third-party astrology API, or some combination — is not stated anywhere on the site. This is a significant omission for any developer building a production astrology product, because the accuracy and reliability of all output flows from this single question.

Feature Comparison

Calculation Methodology: The Question That Matters Most

For any astrology API, the single most important technical question is: where do the numbers come from? Planetary positions, house cusps, ayanamsa values, dasha periods — all downstream output is only as accurate as the ephemeris layer. A wrong ayanamsa value of even 0.3 degrees will put planets in the wrong sign for birth times near sign boundaries, which affects lagna, yoga detection, and dosha classification. This is not a philosophical concern; it is a calculable source of error that affects real users.

Vedika's position is documented and auditable. We run the Swiss Ephemeris C library (the same library used by professional Vedic astrology software worldwide) inside our own Cloud Run containers. The ayanamsa is set to ICRC Lahiri at J2000.0 (23.853222 degrees) using SE_SIDM_USER mode — we have published the exact configuration in our Swiss Ephemeris guide. Our 102 Vedic calculators cover everything from basic planetary positions to Shadbala six-fold strength scores, Naisargika Bala, Drik Bala, and nakshatra pada calculation. The entire calculation stack has been audited against BPHS, Phaladeepika, and Saravali for mathematical accuracy.

RoxyAPI discloses nothing on this topic. There is no mention of Swiss Ephemeris, no statement about ayanamsa handling, no description of the calculation engine. The site lists endpoint names and domain categories but says nothing about what runs behind them. This leaves developers with a structural problem: you cannot evaluate the accuracy of an astrology API if you do not know how it calculates.

There are three possibilities for how RoxyAPI works: they have built their own ephemeris layer (which they would likely advertise); they use the Swiss Ephemeris library without disclosing it; or they proxy another astrology API (Prokerala, AstroAPI, or similar) and add their own request routing on top. The third possibility would make RoxyAPI an API wrapper — a legitimate business model, but one that introduces a dependency on a third party's accuracy, availability, and pricing, which then gets passed through to you.

We cannot determine which of these is true from public information. What we can say is that any developer considering RoxyAPI for production use should ask this question directly before committing to an integration.

AI Chatbot vs MCP Integration: Not the Same Thing

RoxyAPI advertises MCP (Model Context Protocol) support as a headline feature. This is worth understanding precisely, because it is frequently described in a way that sounds like AI capabilities when the two things are different.

MCP is an open protocol, originally developed by Anthropic, that allows AI assistants (like Claude Desktop or other MCP-compatible clients) to call external tools and APIs. RoxyAPI's MCP support means that if you are running an MCP-compatible AI client, you can configure it to pull astrology data from RoxyAPI as one of its tools. This is useful for developers who are already inside an MCP workflow and want to add astrology data to it.

What it is not: a built-in AI that understands astrology, maintains context across a conversation, or can answer natural language questions about a birth chart without the developer providing and configuring an external AI layer. To get AI-powered responses from RoxyAPI's data, you need: an MCP-compatible AI client (subscription or API access to a third-party provider), the correct MCP tool configuration, and your own prompt engineering. The astrology data still comes from RoxyAPI; the AI reasoning comes from somewhere else at your expense and configuration burden.

Vedika's AI chatbot is the opposite architecture. The AI is part of the Vedika API itself. You send a POST request with a birth chart and a natural language question. Vedika computes the chart, runs it through a 6-layer anti-hallucination pipeline (including the Vedika Intelligence Engine, mandatory chart facts, response validation, and post-generation correction), and returns a contextual consultation response. No external AI subscription needed. No prompt engineering required. No MCP client to configure. The endpoint is /api/v1/astrology/query and it accepts any question about the chart in natural language across 30 languages.

The distinction matters for cost accounting: MCP support means the AI cost shows up elsewhere in your infrastructure. Vedika's AI cost is built into the per-query pricing, which makes cost-per-user predictable from day one.

The Pricing Fabrication

RoxyAPI published a comparison article that listed Vedika's pricing as "$7,500 - $22,500/month". This is not a rounding error or a misunderstanding of unit conversion. Vedika's most expensive published plan is $240/month. The $22,500 figure is 93.75 times higher than Vedika's Enterprise plan. The $7,500 figure is 625 times higher than the Starter plan.

There is no conceivable honest source for these numbers. Vedika's pricing has been publicly listed at $12/$60/$120/$240 per month since launch, with no changes. The fabrication appears designed to position RoxyAPI as a lower-cost alternative by inventing a competitor price that does not exist.

Developers evaluating APIs based on cost comparisons from competitor articles should verify prices on the actual pricing pages of each service. For Vedika, that is vedika.io/pricing.

Correct Pricing Comparison

Transparency and Trust Signals

When evaluating a production API dependency, transparency is not a soft criterion. You are building a product that will make API calls to an external service, storing their response data, and presenting it to your users. If that service disappears, changes its API, or raises prices by 10x, your product breaks. The question of who is running the service and whether they are accountable is directly relevant to your production risk.

Team Identity

Vedika is built by XALEN Technology Private Limited, a registered company in Pune, Maharashtra. The founding team is named. Support contacts are available. If something goes wrong, there are humans accountable for it.

RoxyAPI's About page, if it exists, does not surface founder names, company registration, or physical location. The domain registrant is anonymized. This is a legitimate choice for a solo project or stealth-mode startup, but it means there is no public accountability if the service disappears or behaves unexpectedly.

Review Credibility

RoxyAPI displays a 5.0/5.0 aggregate rating from 127 reviews. A perfect 5.0 from 127 reviews is statistically unusual for any real product — some users always report edge cases, integration friction, or documentation gaps. What makes this more notable is that clicking into the rating shows no individual review text, no reviewer names, and no reviewer profiles. The rating is a number with no supporting evidence.

Vedika does not display a star rating on its website, because the user base is still small enough that a meaningful aggregate would not be statistically credible. We have 12 paying customers and 1,500+ registered users. We can name customers and provide references for enterprise inquiries. That is the extent of our verifiable social proof, and we will not inflate it.

Customer Evidence

RoxyAPI's website lists no customer names, case studies, logos, or usage metrics. This is not unusual for a brand-new service. What is unusual is that a 127-review aggregate would require a substantial user base, which does not align with the absence of any customer evidence elsewhere on the site.

Vedika's documented metrics: 1,500+ registered users, 12 paying customers including enterprise integrations, 18,446 real API transactions. These numbers are not designed to impress — they are the honest state of a B2B product in its first year. We publish them because transparency about scale is more useful to developers than fabricated social proof.

Code Comparison

Kundli / Birth Chart — Vedika

// Vedika API — API key in header, ISO datetime format
const response = await fetch('https://api.vedika.io/v2/astrology/kundli', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'x-api-key': 'vk_live_your_key_here'
  },
  body: JSON.stringify({
    datetime: '1995-06-15T14:30:00',
    latitude: 19.0760,
    longitude: 72.8777,
    timezone: '+05:30',
    ayanamsa: 'lahiri'
  })
});

const kundli = await response.json();
// Returns: planets with sign, house, degree, nakshatra, pada, dignity,
// retrograde status, D9/D10 positions, active yogas (21 types),
// Vimshottari dasha periods, house lordships

AI Natural Language Query — Vedika

// Vedika AI Chatbot — no external AI subscription required
const response = await fetch('https://api.vedika.io/api/v1/astrology/query', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'x-api-key': 'vk_live_your_key_here'
  },
  body: JSON.stringify({
    question: 'What does my 10th house placement tell me about career prospects?',
    birthDetails: {
      datetime: '1995-06-15T14:30:00',
      latitude: 19.0760,
      longitude: 72.8777,
      timezone: '+05:30'
    },
    system: 'vedic',   // or 'western', 'kp'
    language: 'en'     // or 'hi', 'ta', 'te', 'bn', 27 other options
  })
});

const consultation = await response.json();
// Returns: natural language analysis grounded in computed chart data.
// AI cannot contradict or fabricate planetary positions — all facts
// come from the Swiss Ephemeris calculation layer.

RoxyAPI — Equivalent Request

// RoxyAPI — exact auth pattern and endpoint structure
// not publicly documented at time of writing.
// Below is an illustrative example based on typical REST API conventions.

const response = await fetch('https://api.roxyapi.com/v1/kundli', {  // endpoint unverified
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': 'Bearer YOUR_ROXY_KEY'  // auth pattern unverified
  },
  body: JSON.stringify({
    date: '1995-06-15',
    time: '14:30',
    latitude: 19.0760,
    longitude: 72.8777,
    // timezone format: unknown
    // ayanamsa options: unknown — not disclosed
  })
});

// Note: calculation methodology not disclosed.
// Accuracy against BPHS standards: unverifiable.

Python SDK — Vedika

# pip install vedika
from vedika import VedikaClient

client = VedikaClient(api_key="vk_live_your_key_here")

# Birth chart in one call
chart = client.kundli(
    datetime="1995-06-15T14:30:00",
    latitude=19.076,
    longitude=72.878,
    timezone="+05:30"
)

print(chart.lagna)          # Ascendant sign
print(chart.planets)        # All planetary positions with dignity
print(chart.active_yogas)   # Detected yogas from 21-type library
print(chart.dasha.current)  # Active Mahadasha / Antardasha

# Natural language query
answer = client.query(
    question="How is Venus influencing my 7th house?",
    chart=chart,
    language="en"
)
print(answer.response)

RoxyAPI has no published Python or JavaScript SDK. Developers integrate via direct HTTP calls with no official client library.

Where Vedika Has Clear Advantages

Where the Comparison Is Genuinely Uncertain

Verdict

When to Choose Each

Questions to Ask Any Astrology API Vendor

Whether you are evaluating Vedika, RoxyAPI, AstroAPI, Prokerala, or any other provider, these are the questions where the answers determine production viability:

1. What is your calculation engine? Do you use Swiss Ephemeris, Moshier, JPL, or a third-party API? Where is the ayanamsa computed and which reference epoch?
2. What ayanamsa values do you support? Can you change it per request or is it global? What is the precision (degrees, minutes, seconds)?
3. Who runs the service? Is there a named company, registered entity, or at minimum a contactable person? What happens to integrations if the service shuts down?
4. What are your uptime SLAs? Do you have a status page with incident history?
5. What are your rate limits? Both per-minute and per-day, across all subscription tiers?
6. What is your pricing? Publicly listed, or "contact sales"? What triggers overages?
7. Can you name a production customer using your API? One verifiable reference case is worth 127 anonymous review stars.

Frequently Asked Questions