Vedaksha
Supports deployment to Cloudflare Workers edge computing platform using the AnalyticalProvider ephemeris for zero-data environments.
Provides Docker container deployment for the MCP server with HTTP transport on port 3100.
Supports macOS arm64 platform with pre-built Python wheels available via PyPI installation.
Provides Python package distribution through PyPI for Python bindings installation and usage.
Provides Python bindings via PyO3 for chart computation and Vedic astrology functionality.
Provides native Rust crates for astronomical ephemeris computation and Vedic astrology platform functionality.
Provides WebAssembly bindings for browser-based chart computation with 972KB binary and zero data files.
Vedākṣha — Vision from Vedas
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
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 # WebAssemblyWhy 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. SeeDATA_PROVENANCE.mdanddocs/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 |
Umbrella crate — | |
Chebyshev polynomials, angle arithmetic, interpolation, rotation matrices | |
JPL DE440 SPK reader, AnalyticalProvider (VSOP87A + ELP/MPP02), coordinate pipeline, precession, nutation, ΔT | |
10 house systems, 44 ayanamshas (IAU 2006 P03 5th-order), aspects, dignities, transits | |
27 nakshatras, 5 dasha systems, 16 vargas, 50 yogas, Shadbala | |
Property-graph ontology (10 node types, 13 edge types) + Cypher / SurrealQL / JSON-LD emitters | |
Model Context Protocol server — 12 JSON-RPC tools for AI agents | |
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, |
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 coordinatesZero-data path (WASM / edge):
VSOP87A / ELP coefficients (compiled) → Poisson series evaluation
→ heliocentric ecliptic → equatorial rotation → barycentric ICRS
→ same downstream pipelineDelta 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-mcpThe 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 |
| full pipeline |
Python |
| PyO3, type stubs |
WASM |
| browser & edge, no data files |
MCP |
| 12 tools, stdio + HTTP |
Docker |
| 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.
Copyright © 2026 ArthIQ Labs LLC · Licensed under BSL 1.1.
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