Bring the profound wisdom of Vedic Astrology to your AI agents via the Model Context Protocol.
Project description
RishiAI MCP Server
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" |
natal_chart_json |
string | Full JSON output from cast_vedic_chart |
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
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