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AI Product Integration

This guide covers using Asterwise as the calculation backbone for AI-powered astrology products — chatbots, personalised recommendation engines, and AI assistants.

Why use Asterwise with AI​

AI language models have no astronomical calculation capability. They cannot compute planetary positions, dasha timelines, or yoga detection from birth data. Asterwise provides the calculation layer; your AI provides the interpretation and conversational layer.

The pattern is:

  1. User provides birth details
  2. Your AI calls Asterwise endpoints
  3. Asterwise returns structured data
  4. Your AI interprets and explains the results

Start with the natal chart and build context progressively:

# Step 1 — natal chart gives you the foundation
POST /v1/astro/natal

# Step 2 — yogas for positive combinations
POST /v1/astro/yoga

# Step 3 — doshas for afflictions
POST /v1/astro/dosha

# Step 4 — active dasha for timing
POST /v1/astro/dasha (levels: 2)

# Step 5 — current transits
POST /v1/astro/gochar

Pass include_interpretation: true on the natal endpoint to get pre-written interpretation text for the ascendant, Moon sign, and nakshatra — your AI can use these as context for richer responses.

Using the MCP server​

If you are building with Claude, Cursor, or any MCP-compatible AI, connect the Asterwise MCP server directly:

  • MCP URL: https://mcp.asterwise.com/mcp
  • Auth: OAuth 2.1 with authorization_code + PKCE

See the MCP Setup Guide for full connection instructions. With MCP connected, your AI can call all 103 Asterwise tools natively without writing any API integration code.

Response format for AI consumption​

All endpoints support response_format: json for structured parsing or response_format: markdown for human-readable output. For AI pipelines, use json and let your AI model interpret the structured fields.