ai-divination-mcp
Allows OpenAI agents (e.g., Codex) to use divination tools via the MCP server.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@ai-divination-mcpDraw three tarot cards about my conflicting career path."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
AI Divination Skills
✨ Open-source divination skills for AI agents where the tool performs the draw or cast, and AI interprets the concrete result.
ai-divination-skills is a practical skill collection for tarot, I Ching, Xiao Liu Ren, and future symbolic systems. It is built for agent workflows that need auditable randomness, clear method boundaries, and reusable interpretation templates.
This project treats divination as symbolic reasoning and reflection, not deterministic prediction.
⚡ One-line Install for AI Agents
Paste this into your AI agent:
Install AI Divination Skills for this agent: https://raw.githubusercontent.com/sapuyou45-bit/ai-divination-skills/main/docs/install.mdOr install directly for Claude-style local skills:
curl -fsSL https://raw.githubusercontent.com/sapuyou45-bit/ai-divination-skills/main/install.sh | bashThe default target is ~/.claude/skills. Set AI_SKILLS_DIR for another agent skill directory.
Related MCP server: Unified MCP Server
✨ Overview
Most AI divination prompts let the model invent the result. This repo separates the two jobs:
A local script produces the card draw, hexagram, or Xiao Liu Ren position.
The AI agent interprets that generated result with clear safety boundaries.
That makes readings easier to test, reproduce, audit, and reuse across agents.
🧭 Methodological Rigor
The core rule is simple: scripts or user-provided physical casts generate the divination result; AI interprets that result and does not generate the divination result.
This is not scientific proof of divination efficacy. It is a stricter workflow for symbolic reasoning:
real readings use system randomness by default
seeded mode is only for tests and reproducible demos
traditional methods and limitations are documented per skill
JSON outputs include enough metadata to audit the method
approximate modes emit warnings instead of pretending to be traditional
🌐 Multilingual Docs
The GitHub Pages site now defaults to Simplified Chinese. Use the page header switcher there when you want English or Japanese.
Local preview:
python3 -m http.server 8000 -d docsPublished site:
https://sapuyou45-bit.github.io/ai-divination-skills/🧩 Included Skills
Skill | What it does | Script |
| Draws tarot cards for reflection, decisions, creative blocks, and project reframing. |
|
| Casts six-line I Ching hexagrams with primary and resulting hexagrams. |
|
| Casts Xiao Liu Ren from lunar-style numbers or a Gregorian time fallback. |
|
| Casts a Bazi (Four Pillars / 八字) chart from a Gregorian birth datetime. Requires the optional |
|
🚀 Quick Start
Install from PyPI:
pip install ai-divination-skillsOr from a checkout:
pip install .Use editable mode while developing:
pip install -e .Use one command for every system:
ai-divination tarot --deck major --spread three-card --reversals
ai-divination iching --method yarrow
ai-divination xiaoliuren --method numbers --month 3 --day 12 --hour 7Ask for an agent interpretation template:
ai-divination template tarotUse the Python API directly:
from ai_divination_skills.tarot import draw
from ai_divination_skills.iching import cast
from ai_divination_skills.xiaoliuren import cast_numbersYou can still run the underlying scripts directly:
python3 skills/tarot/scripts/draw.py --deck major --spread three-card --reversals
python3 skills/iching/scripts/cast.py --method coins
python3 skills/iching/scripts/cast.py --method yarrow
python3 skills/xiaoliuren/scripts/cast.py --method numbers --month 3 --day 12 --hour 7Use a seed for reproducible demos:
python3 skills/tarot/scripts/draw.py --spread decision --seed demo
python3 skills/iching/scripts/cast.py --method yarrow --seed demoAll scripts output JSON.
📦 Install as Agent Skills
For AI-agent-guided setup, use the remote install runbook:
Install AI Divination Skills for this agent: https://raw.githubusercontent.com/sapuyou45-bit/ai-divination-skills/main/docs/install.mdFor direct shell install:
curl -fsSL https://raw.githubusercontent.com/sapuyou45-bit/ai-divination-skills/main/install.sh | bashThe installer copies tarot, iching, and xiaoliuren into ~/.claude/skills by default. To target another agent, set AI_SKILLS_DIR before running it.
Manual install is just copying the folders you want into your agent's skill directory:
mkdir -p ~/.claude/skills
cp -R skills/tarot ~/.claude/skills/tarot
cp -R skills/iching ~/.claude/skills/iching
cp -R skills/xiaoliuren ~/.claude/skills/xiaoliurenEach skill is self-contained:
skills/name/
SKILL.md
agents/openai.yaml
scripts/
references/Install individual folders, not the entire repository, when you only want one skill.
Each skill script also works in single-folder mode. If the Python package is installed, the script delegates to the package runtime. If only the skill folder is copied, it falls back to the bundled standalone script in that skill.
Per-host adapters
Every skill ships four adapter files in skills/<skill>/agents/:
Host | File | How it is invoked |
OpenAI / Codex skills |
| Skill metadata + brand icons. |
Claude Desktop / claude.ai project skills |
| Tool spec that runs |
Gemini CLI / Gemini Extensions |
| Extension manifest that runs the same CLI. |
Cursor |
| Rule file with hard "never invent the draw" guard. |
All four adapters route through the same audited ai-divination <skill> CLI, so the agent host never invents the result.
🧠 Use it from Claude Desktop / Codex / any MCP host
ai-divination-skills ships a built-in MCP server (ai-divination-mcp). Any
Model Context Protocol host — Claude Desktop, Codex,
Continue, Cursor — can mount it with a single config line, and the model gets five tools:
tarot.draw, iching.cast, xiaoliuren.cast, bazi.cast, and interpretation_template.
The model never invents the draw; the server runs the audited scripts locally.
Claude Desktop
Install the package once:
pip install ai-divination-skillsThen edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or
%APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"divination": {
"command": "ai-divination-mcp"
}
}
}Restart Claude Desktop. Ask "draw three tarot cards for my decision" — Claude will call
tarot.draw and interpret the JSON output.
Codex / Continue / Cursor
Any MCP-aware host follows the same pattern. The server speaks JSON-RPC 2.0 over stdio with no third-party dependencies.
Per-client setup guides
Copy-paste JSON configs and example prompts for each host:
🤖 Agent Behavior
Each skill instructs the agent to:
generate or accept a concrete draw/cast result
read concise reference material only when needed
interpret with the shared response contract
avoid certainty, fatalism, and professional advice
Shared guidance lives in:
shared/methodology.mdshared/interpretation-protocol.mdshared/response-contract.mdshared/randomness-protocol.mdshared/safety-policy.mdshared/interpretation-style.md
🧪 Examples
examples/tarot-decision.mdexamples/iching-strategy.mdexamples/xiaoliuren-daily.md
🛡️ Safety Boundaries
These skills are not for medical, legal, financial, or crisis guidance.
Good readings should:
frame the result as symbolic reflection
connect claims to the generated result
preserve user agency
offer small, reversible next steps
state uncertainty clearly
See ETHICS.md for the full project stance.
🛠️ Development
No runtime dependencies are required beyond Python 3.
Run tests:
python3 -m unittest discover -s testsCurrent coverage checks:
unified CLI routing
package-only CLI execution
importable Python APIs
single-folder skill execution
skill metadata and asset contracts
interpretation protocol templates
tarot spread output
I Ching cast structure and manual lines
Xiao Liu Ren number and time fallback behavior
💬 Community
Releases: https://github.com/sapuyou45-bit/ai-divination-skills/releases
Roadmap:
ROADMAP.mdDiscussions: https://github.com/sapuyou45-bit/ai-divination-skills/discussions
Issues: pick a
good first issueor propose anew-skillSecurity: see
SECURITY.mdfor private vulnerability reporting
🗺️ Roadmap
Near-term:
Add a published package workflow.
Expand automated skill validation in CI.
Add richer reference material for each MVP skill.
Add more example readings.
Add more agent integration examples.
Later:
meihualiuyaorunesnumerologyastrology
📄 License
MIT
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