Vedaksha

Clean-room Rust ephemeris and Vedic astrology engine, built for the agentic-AI era. Sub-arcsecond planetary precision, every algorithm traced to a primary source, every chart emitted as a queryable property graph.

Celestial computation. Agentic precision.

Website · Docs · Playground · API reference · Blog

clean-room · sub-arcsecond vs JPL Horizons · 870 tests + 8,700 oracle rows · MCP-native · BSL 1.1 → Apache 2.0

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Quick start

use vedaksha::prelude::*;

let jd = calendar_to_jd(2024, 3, 20, 12.0);
let chart = compute_chart(jd, 28.6139, 77.2090, &ChartConfig::vedic());

cargo add vedaksha          # Rust
pip install vedaksha        # Python (PyO3)
npm install vedaksha-wasm   # WebAssembly

Why Vedākṣha

• Clean-room, cited. Every module that implements a cited algorithm carries a // Source: doc-comment pointing at the primary paper or treatise (VSOP87A, ELP/MPP02, IAU standards, BPHS, Jaimini) — never derived from other software, no GPL contamination. See DATA_PROVENANCE.md and docs/audit/.
• Sub-arcsecond, proven. Validated against JPL Horizons / DE441 — 870 tests plus 8,700 oracle reference rows on every CI run, on both Ubuntu and macOS.
• Agentic-AI-native. A 12-tool Model Context Protocol server, and every chart is a property graph you can query in Cypher, SurrealQL, or JSON-LD.
• Runs everywhere. One Rust codebase → native, Python, WebAssembly (no data files), and a containerized MCP server. No FFI to a C library, no platform-specific build.
• Jyotish in the type system. Nakshatras, dashas, vargas, yogas, shadbala, ayanamshas — first-class, not a Western afterthought.

Workspace

Crate	Description
vedaksha	Umbrella crate — prelude, compute_chart, ChartConfig. Optional locale feature (7 languages: en · hi · sa · ta · te · kn · bn).
vedaksha-math	Chebyshev polynomials, angle arithmetic, interpolation, rotation matrices
vedaksha-ephem-core	JPL DE440 SPK reader, AnalyticalProvider (VSOP87A + ELP/MPP02), coordinate pipeline, precession, nutation, ΔT
vedaksha-astro	10 house systems, 44 ayanamshas (IAU 2006 P03 5th-order), aspects, dignities, transits
vedaksha-vedic	27 nakshatras, 5 dasha systems, 16 vargas, 50 yogas, Shadbala
vedaksha-graph	Property-graph ontology (10 node types, 13 edge types) + Cypher / SurrealQL / JSON-LD emitters
vedaksha-mcp	Model Context Protocol server — 12 JSON-RPC tools for AI agents
vedaksha-wasm	WebAssembly bindings — full chart computation in the browser, no data files

Python bindings via PyO3 live in bindings/python.

Two ephemeris providers

Provider	Accuracy	Data	Use case
SpkReader	Sub-arcsecond	DE440s (~31 MB on disk)	Servers, containers
AnalyticalProvider	<15″ planets, <1″ Moon	Zero files (compiled constants)	WASM, edge, Cloudflare Workers, no_std

The AnalyticalProvider evaluates VSOP87A (Bretagnon & Francou 1988) for planets and ELP/MPP02 (Chapront 2002) for the Moon — all coefficients are compile-time constants, so there are no runtime data files.

Computation pipeline

JPL DE440 SPK → Chebyshev evaluation → ICRS barycentric
  → light-time correction → precession (IAU 2006 P03, 5th-order)
  → nutation (IAU 2000B) → frame bias (ICRS→J2000)
  → aberration → ecliptic coordinates

Zero-data path (WASM / edge):

VSOP87A / ELP coefficients (compiled) → Poisson series evaluation
  → heliocentric ecliptic → equatorial rotation → barycentric ICRS
  → same downstream pipeline

Delta T: IERS measured table (1620–2025) + Espenak–Meeus predictions to 2050.

Vedic astrology

First-class Jyotish, drawn from primary classical sources.

• Nakshatras — 27 lunar mansions with padas, lords, symbols, deities
• Dashas — Vimshottari (120-yr), Yogini (36-yr), Ashtottari (108-yr), and Chara & Narayana (Jaimini, sign-based)
• Vargas — all 16 divisional charts (D-1 Rashi → D-60 Shashtiamsha)
• Yogas — 50 classical combinations (Pancha Mahapurusha, Dhana, Raja, Daridra, …)
• Shadbala — complete six-component planetary strength, with Ishta / Kashta phala
• Ayanamsha — 44 sidereal systems (Lahiri, Raman, KP, Fagan-Bradley, +40)
• Lunar nodes — Mean, True (Meeus 5-term, ~0.09°), and Osculating (<0.03° vs JPL DE441) — KP sub-lord ready
• Panchanga — full five limbs: Tithi (paksha, lord), Vara (Rahu / Gulika Kalam), Nakshatra (deity, yoni, nadi), Yoga (27), Karana (60)
• Drishti — graded aspects: Full, ¾ (75%), ½ (50%), ¼ (25%) per BPHS Ch. 26

AI-native: MCP + property graph

Every computation produces a property graph, not flat structs — so an agent can ask "which planets aspect the 7th-house lord?" as a graph query instead of re-implementing chart logic. The MCP server exposes 12 tools, discoverable with a single tools/list call:

compute_natal_chart · compute_dasha · compute_vargas · compute_karakas · compute_combustion · compute_shadbala · compute_ashtakavarga · compute_transit · compute_gochara · search_transits · search_muhurta · emit_graph

cargo install vedaksha-mcp
vedaksha-mcp                      # stdio (Claude Desktop, Cursor, VS Code)
vedaksha-mcp --http --port 3100   # HTTP transport
docker run -p 3100:3100 ghcr.io/arthiqlabs/vedaksha-mcp

The tool surface is generated from the Rust definitions and locked by a snapshot test, so the published catalog can't silently drift from the code.

Accuracy

Validated against two independent reference ephemerides across 8,700 oracle reference rows in tests/oracle_jpl/:

Metric	SpkReader (DE440s)	AnalyticalProvider
Planetary longitude	Sub-arcsecond (avg 1.7″)	<15″ (avg 3.8″)
Moon longitude	Sub-arcsecond	<1″ (0.23″ avg, 0.60″ max, 1900–2100 vs JPL Horizons)
House cusps (10 systems)	<0.001°	<0.01°
Ayanamsha (44 systems)	avg 0.005°	same (pure math)
Dasha periods	Sum to 120 yr ± 0.01 days	same
Nakshatra boundaries	Reference-accurate	matches SpkReader

Install

Platform	Install	Notes
Rust	cargo add vedaksha	full pipeline
Python	pip install vedaksha	PyO3, type stubs
WASM	npm install vedaksha-wasm	browser & edge, no data files
MCP	cargo install vedaksha-mcp	12 tools, stdio + HTTP
Docker	docker run ghcr.io/arthiqlabs/vedaksha-mcp	MCP server on port 3100

Published: crates.io — 7 crates (vedaksha, vedaksha-math, vedaksha-ephem-core, vedaksha-astro, vedaksha-vedic, vedaksha-graph, vedaksha-mcp) · PyPI vedaksha · npm vedaksha-wasm · Docker ghcr.io/arthiqlabs/vedaksha-mcp.

License

Business Source License 1.1.

• Non-commercial use — free (personal projects, research, education, internal tools).
• Commercial use — $500 one-time per organization. Purchase →
• Converts to Apache 2.0 five years after each version's release date.

See LICENSE for full terms.

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Copyright © 2026 ArthIQ Labs LLC · Licensed under BSL 1.1.