AstroNest — Vedic Astrology Readings MCP server

AstroNest: Vedic astrology for apps and AI agents

AstroNest is a Vedic astrology (Jyotiṣa) engine you can call as a REST API or connect to an AI agent over MCP. It computes on its own JPL DE440 ephemeris, and the readings are deterministic: the same birth data always gives the same answer, with the reasons and the classical books each reading rests on.

This repository has two things: how to connect AstroNest to an AI agent, and a Next.js quickstart on the REST API.

• Docs:
• OpenAPI 3.1 spec:
• Postman: AstroNest Developer API workspace
• Keys: . Sandbox keys are free and return fixed samples.

Connect it to an AI agent (MCP)

Endpoint (Streamable HTTP): https://www.astronest.ai/api/developer/mcp

Claude Code

claude mcp add --transport http astronest https://www.astronest.ai/api/developer/mcp \
  --header "Authorization: Bearer YOUR_ASTRONEST_KEY"

mcp.json (Cursor, VS Code and other clients that read this format)

{
  "mcpServers": {
    "astronest": {
      "url": "https://www.astronest.ai/api/developer/mcp",
      "headers": { "Authorization": "Bearer YOUR_ASTRONEST_KEY" }
    }
  }
}

Also on Smithery and the MCP Registry as io.github.onedotlinks/astronest.

What an agent can ask it

Each tool answers one question. The interpretive ones read the chart the way a practitioner does and return the reasons, not just positions:

The readings describe what the chart shows and why. They are symbolic interpretation, not predictions, and not medical, legal, financial or psychological advice; every response carries that disclaimer.

The Next.js quickstart

A small Next.js app on the AstroNest Developer API. Enter a birth date, time and place and get:

timing windows and how many methods agree (5 credits)

• the chart: lagna, the nine grahas with sign, house, nakṣatra and dignity, and the running daśā (1 credit)
• guidance now: plain-language cards for the running mahādaśā / antardaśā / pratyantardaśā (3 credits)
• a domain reading: career, marriage, finance and twelve more, with supporting factors, cautions,

• optionally, "explain in plain words" with your own LLM (0 AstroNest credits)

None of the three AstroNest calls uses a language model. They are deterministic, so they return in seconds and the same input always gives the same answer.

Run it in five minutes

Shortened. The full README is on GitHub.