Skip to main content

Bring the profound wisdom of Vedic Astrology to your AI agents via the Model Context Protocol.

Project description

RishiAI MCP Server

PyPI version CI Python versions License: MIT

A Model Context Protocol server that exposes Vedic astrology tools powered by the DashaFlow calculation engine.

Works with any MCP-compatible client — VS Code Copilot, Cursor, Claude Desktop, Claude Code, Gemini CLI, Codex, Antigravity, OpenCode, OpenClaw, Pi agent, or any custom app that speaks MCP.

Install

pip install rishi-ai-mcp

Quick Start

rishi-ai-mcp                    # console entry point (after pip install)
python rishi_ai_mcp.py          # or run directly from source

Communicates over stdio. Any MCP client that can spawn a subprocess and speak MCP can use it — no IDE required.


Setup

Clone this repo into your workspace to get the MCP config + RishiAI agent rules for your IDE:

git clone https://github.com/adarshj322/rishi-ai-mcp.git

The repo includes ready-to-use configs for three IDEs:

VS Code / GitHub Copilot

  • .vscode/mcp.json — auto-configures the MCP server
  • .github/copilot-instructions.md — RishiAI persona (always-on)
  • .agents/skills/*/SKILL.md — 12 workflow skills (auto-triggered by topic, or invoke via /skill-name)

VS Code Copilot reads .github/copilot-instructions.md for always-on instructions and .agents/skills/ for skills. Just open the cloned folder and the tools + persona + skills are active.

Cursor

  • .cursor/mcp.json — auto-configures the MCP server
  • .cursor/rules/rishi-ai.mdc — RishiAI persona (always-on core rule)
  • .agents/skills/*/SKILL.md — 12 workflow skills (shared, Cursor reads .agents/skills/ natively)

Open the cloned folder in Cursor and the tools + persona + skills are active.

Antigravity

  • .agents/rules/rishi-ai.md — RishiAI persona (always-on)
  • .agents/skills/*/SKILL.md — 12 workflow skills
  • .agents/workflows/*.md — 12 slash-command workflows

Antigravity reads .agents/ natively. Configure the MCP server in your Antigravity settings:

command: uvx
args: rishi-ai-mcp

Other MCP Clients (Claude Desktop, Claude Code, Gemini CLI, etc.)

Any MCP-compatible client can connect using the same server. Add to your client's MCP config:

{
  "mcpServers": {
    "vedic-astrology": {
      "command": "uvx",
      "args": ["rishi-ai-mcp"]
    }
  }
}

For the RishiAI persona, use system_prompt.md as a reference and adapt it to your client's instruction format.

Standalone / Custom Client

from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client

params = StdioServerParameters(command="uvx", args=["rishi-ai-mcp"])

async with stdio_client(params) as (read, write):
    async with ClientSession(read, write) as session:
        await session.initialize()
        result = await session.call_tool("cast_vedic_chart", {
            "dob": "1990-04-15", "time": "14:30",
            "lat": 28.6139, "lon": 77.2090, "timezone": "Asia/Kolkata"
        })
        print(result)

MCP Tools

cast_vedic_chart

Generates a complete Vedic natal chart.

Parameter Type Description
dob string Date of birth — "YYYY-MM-DD"
time string Time of birth — "HH:MM" (24-hour)
lat float Birth latitude (e.g. 28.6139 for Delhi)
lon float Birth longitude (e.g. 77.2090 for Delhi)
timezone string IANA timezone (e.g. "Asia/Kolkata")
query_date string Optional — date for Dasha lookup, defaults to today

Returns: JSON with metadata, panchang, lagna (with D2–D60 signs), planets (with dignity, combustion, Shadbala, all 14 Varga signs, aspects), dashas (5 levels: Maha/Antar/Pratyantar/Sukshma/Prana + timeline), yogas (24 types), ashtakavarga (SAV + BAV + Prashtara), jaimini_karakas, shadbala (with Ishta/Kashta Phala), bhava_chalit, avasthas, kaal_sarpa, graha_yuddha, gandanta, arudha_padas (A1–A12), upapada, karakamsha.

cast_transit_chart

Calculates planetary transits overlaid on a natal chart.

Parameter Type Description
transit_date string Date to compute transits — "YYYY-MM-DD"
dob string Date of birth — "YYYY-MM-DD"
time string Time of birth — "HH:MM" (24-hour)
lat float Birth latitude
lon float Birth longitude
timezone string Optional — defaults to "Asia/Kolkata"

Returns: JSON with transit planets (sign, degree, nakshatra, sav_points, house from Lagna/Moon), sade_sati status and phase, and rahu_ketu_axis.

calculate_compatibility_tool

Calculates 16-factor compatibility + Kuja Dosha. Person 1 = Male, Person 2 = Female.

Parameter Type Description
dob1, time1, lat1, lon1, tz1 various Birth details for Person 1 (Male)
dob2, time2, lat2, lon2, tz2 various Birth details for Person 2 (Female)

Returns: 8 Ashtakoot kutas (36 pts), additional kutas (Mahendra, Stree Deergha, Vedha, Rajju, BadConstellations, LagnaHouse7, SexEnergy), exception logic, and Kuja Dosha analysis.

check_muhurtha_tool

Evaluates whether a date/time is auspicious for a specific activity (electional astrology).

Parameter Type Description
activity string One of: marriage, travel, business, education, house_entry, medical
date string Date to evaluate — "YYYY-MM-DD"
time string Time to evaluate — "HH:MM" (24-hour)
lat float Location latitude
lon float Location longitude
timezone string IANA timezone string

Returns: JSON with verdict, score, positive_factors, negative_factors, panchang_suddhi, and marriage_doshas (for marriage activity).

analyze_career_chart

Analyzes career potential using the 10th house, D10 Dashamsha, and planetary significations.

Parameter Type Description
dob string Date of birth — "YYYY-MM-DD"
time string Time of birth — "HH:MM" (24-hour)
lat float Birth latitude
lon float Birth longitude
timezone string IANA timezone string

Returns: JSON with tenth_house info, d10_indicators, career_themes, and strength_factors.


RishiAI Agent Persona

The repo includes the RishiAI persona — a Vedic astrologer AI that interprets chart data using BPHS methodology.

IDE Always-on Rule Skills
VS Code Copilot .github/copilot-instructions.md .agents/skills/*/SKILL.md (12 skills)
Cursor .cursor/rules/rishi-ai.mdc .agents/skills/*/SKILL.md (12 skills)
Antigravity .agents/rules/rishi-ai.md .agents/skills/*/SKILL.md + .agents/workflows/*.md
Other clients Adapt from system_prompt.md Adapt workflow steps from .agents/workflows/

All IDEs share skills from .agents/skills/ using the Agent Skills open standard.

Workflows

Command Description
/full-reading Complete natal chart reading
/career-analysis Career and professional guidance
/marriage-analysis Marriage timing and compatibility
/relationship-analysis Relationship dynamics
/children-analysis Children and progeny
/finance-analysis Wealth and financial prospects
/health-analysis Health tendencies and remedies
/education-analysis Education and learning
/spiritual-analysis Spiritual path and practices
/muhurtha-analysis Electional astrology timing
/physicalIntimacy-analysis Physical compatibility
/geopolitics-analysis Mundane astrology

Architecture

rishi_ai_mcp.py            MCP entry point — 5 tools, pip-installable
  └── dashaflow (pip)      Calculation engine
        ├── vedic_calculator   Swiss Ephemeris core
        ├── constants          Zodiac, nakshatras, dignities
        ├── nakshatra          Nakshatra lookup
        ├── panchang           Tithi, Vara, Yoga, Karana
        ├── yoga               24 yoga types + Kaal Sarpa, Graha Yuddha, Gandanta
        ├── dasha              Vimshottari 5-level
        ├── dignity            Dignity, combustion, digbala
        ├── ashtakavarga       SAV, BAV, Prashtara
        ├── jaimini            Karakas, Arudha Padas, Upapada, Karakamsha
        ├── shadbala           Six-fold strength + Ishta/Kashta
        ├── matchmaking        16-factor compatibility + Kuja Dosha
        ├── muhurtha           Electional astrology
        └── career             D10 career analysis

.vscode/mcp.json           VS Code Copilot MCP config
.github/
  └── copilot-instructions.md  Always-on rule (VS Code Copilot)
.cursor/
  ├── mcp.json             Cursor MCP config
  └── rules/rishi-ai.mdc   Always-on core rule (Cursor)
.agents/                   Shared across all IDEs
  ├── rules/rishi-ai.md   Always-on agent rule (Antigravity)
  ├── skills/              12 workflow skills (SKILL.md per folder)
  └── workflows/           12 slash-command workflows (Antigravity)
system_prompt.md           Universal reference prompt (for other clients)

Prerequisites

  • Python 3.10+
  • dashaflow — installed automatically as dependency
  • mcp — installed automatically as dependency

License

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

rishi_ai_mcp-1.1.0.tar.gz (44.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

rishi_ai_mcp-1.1.0-py3-none-any.whl (10.0 kB view details)

Uploaded Python 3

File details

Details for the file rishi_ai_mcp-1.1.0.tar.gz.

File metadata

  • Download URL: rishi_ai_mcp-1.1.0.tar.gz
  • Upload date:
  • Size: 44.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for rishi_ai_mcp-1.1.0.tar.gz
Algorithm Hash digest
SHA256 a746e90a628c7cbca48afe2aa1fc9f04522b0ef201989727d6c74a4f61cf202f
MD5 4b2203a4090086895bd66ed051a1e0e5
BLAKE2b-256 67597ff352a4c740ba0615bd40714e2bffab3fcd6274f343da9d52ddcbd18078

See more details on using hashes here.

Provenance

The following attestation bundles were made for rishi_ai_mcp-1.1.0.tar.gz:

Publisher: publish.yml on adarshj322/rishi-ai-mcp

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file rishi_ai_mcp-1.1.0-py3-none-any.whl.

File metadata

  • Download URL: rishi_ai_mcp-1.1.0-py3-none-any.whl
  • Upload date:
  • Size: 10.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for rishi_ai_mcp-1.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 763d287aa7c5f645ba2d9031f15dfc33f49a58b357fadd7a07c86e411c4fe2d7
MD5 f01fdcbf3e0e806ed2a5d28303ff5ea7
BLAKE2b-256 8fbc6d4a42e5a21a43d136438ba92bc3a41dc83194e6d2f215529b876a880437

See more details on using hashes here.

Provenance

The following attestation bundles were made for rishi_ai_mcp-1.1.0-py3-none-any.whl:

Publisher: publish.yml on adarshj322/rishi-ai-mcp

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page