Astro Skill MCP Server
Provides Vedic astrology calculations (kundali, dasha, panchang, yoga) and Hindi/English PDF reports via 11 MCP tools, with SQLite-backed client/report storage.
README
Astro Skill
Portable Vedic astrology engine, agent skill, and MCP server. Deterministic kundali, dasha, panchang, and yoga calculations with JSON and Hindi/English PDF reports — reusable by any agent or MCP-compatible client.
<p align="center"> <img src="docs/images/sample-cover-hi.png" alt="Hindi PDF report cover" width="330"> <img src="docs/images/sample-lagna-chart.png" alt="North Indian lagna kundali chart" width="330"> </p> <p align="center"> <img src="docs/images/sample-dasha-strip.png" alt="Vimshottari dasha timeline" width="670"> </p>
The repo is split so each layer can be reused on its own:
astro/— the portable skill: calculator scripts, reference data, bundled Swiss Ephemeris + Devanagari font, and tests. Drop it into any agent or call the scripts directly from Python.services/astro_mcp/— a generic stdio MCP server exposing the same calculations plus SQLite storage as 11 stable tools.apps/— optional products built on top (e.g. a web panel scaffold).docs/— architecture, roadmap, deployment, and operations docs.
Features
- Kundali — lagna, rashi, nakshatra + pada, nine grahas (with retrograde), whole-sign houses, and dosha flags (e.g. Mangalik).
- Navamsa (D9) divisional chart in both JSON and the PDF report.
- Vimshottari dasha — mahadasha + antardasha timeline with correct birth-balance handling (the sub-period actually running at birth, not a fresh lord/lord cycle).
- Daily Panchang — tithi, vara, nakshatra, yoga, karana, sunrise/sunset — anchored at sunrise (classical convention), with muhurta and yoga detection.
- Lahiri (Chitrapaksha) sidereal positions, whole-sign houses.
- High precision — bundled Swiss Ephemeris
.se1data (SWIEPH) with an automatic Moshier fallback; each output records the tier used incalculation.ephemeris. - Reports — structured JSON, and PDF via a preferred HTML/Chromium renderer
(polished Devanagari) or a legacy in-process ReportLab fallback. Hindi/English,
with a bundled Noto Sans Devanagari font. The HTML renderer also supports a
pandit_v1premium template for pitch-ready operator reports. - MCP server — 11 tools over stdio, with SQLite-backed client/report storage, input validation, and traversal-safe report filenames.
Quick start
git clone https://github.com/adityarya24/astro-skill.git
cd astro-skill
python -m venv .venv && . .venv/bin/activate # Windows: .\.venv\Scripts\Activate.ps1
python -m pip install --upgrade pip
pip install -e ".[dev]"
# Optional: Chromium for the preferred HTML PDF renderer
python -m playwright install chromium
# Checks
python -m pytest -q
python -m ruff check astro services scripts
All tests pass; the HTML/Chromium PDF render test skips automatically until
Chromium is installed. For OS-specific venv details and MCP client config
examples, see docs/operations/install-smoke.md.
MCP server
services/astro_mcp/ is an importable package and a runnable stdio MCP
server. The same TOOLS registry powers the unit tests and the wire protocol
— no duplicated logic, and no environment variables required.
Tools (11): parse_birth_details, save_client_profile, find_client_profile,
list_client_reports, calculate_kundali, calculate_dasha,
calculate_gochar, calculate_compatibility, calculate_panchang,
generate_report_json, generate_pdf_report.
python -m services.astro_mcp # or `astro-mcp` after `pip install -e .`
Wire it into any MCP client (Claude Desktop, a Codex agent, or your own) by
pointing the client's MCP config at that command with cwd set to the repo
root. See services/astro_mcp/README.md for the
tool contract and config examples, and verify an install in one shot with:
python scripts/smoke_mcp_client.py
Sample commands
# Kundali JSON
python astro/scripts/kundali_calculator.py --dob 26/12/2019 --tob 09:15 \
--place Delhi --lat 28.6139 --lon 77.2090 --timezone Asia/Kolkata --json
# Panchang JSON
python astro/scripts/panchang_calculator.py --date 2026-05-21 \
--place Delhi --lat 28.6139 --lon 77.209 --timezone Asia/Kolkata --json
# Hindi PDF (default HTML/Chromium renderer; add --renderer reportlab for the
# no-browser fallback)
python astro/scripts/pdf_report.py --kundali-json chart.json --dasha-json dasha.json \
--panchang-json panchang.json --output report.pdf --language hi
# Pandit-style report
python astro/scripts/pdf_report.py --kundali-json chart.json --dasha-json dasha.json \
--panchang-json panchang.json --output pandit-v1.pdf --language hi \
--template pandit_v1 --client-name "Client Name"
Deployment
Run it as a Docker MCP server (the image bundles Python, dependencies, Chromium,
the Devanagari font, and the ephemeris data) or straight from Python. See
docs/deploy.md for build, run, smoke-test, and MCP-client
wiring instructions.
Documentation
docs/operations/install-smoke.md— fresh-clone install, MCP client config, smoke checklist.docs/deploy.md— Docker / MCP-client deployment.docs/architecture/generic-astro-platform.md— layering and reuse model.docs/architecture/astro-skill-roadmap.md— engine roadmap.services/astro_mcp/README.md— MCP server contract.astro/SKILL.md— agent skill instructions.
Production notes
- Positions use the bundled high-precision Swiss Ephemeris (SWIEPH) out of the box, not the lower-precision Moshier fallback.
- The default PDF path is HTML/Chromium for production Hindi rendering; ReportLab stays as a no-browser fallback.
- Generated runtime data lives under an ignored
data/directory (or a caller-provided output directory). - MCP tools validate their JSON schemas and keep generated filenames detached from caller-controlled identifiers.
- GitHub Actions runs install, Chromium setup, tests, ruff, and skill validation on push and pull requests.
Safety boundaries
These rules apply across every layer and downstream product:
- Reports are calculation-backed drafts, intended for review by an astrologer or operator before any final reading is shared.
- Missing birth details must be requested rather than guessed.
- Approximate or partial inputs must be marked clearly in any output.
- Do not generate death, accident, medical, or unavoidable-harm certainty predictions.
License
MIT — see LICENSE.
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