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PlantOntology

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Enables querying a plant knowledge graph for companion planting, climate suitability, and landscape design recommendations via natural language.

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Описание

Enables querying a plant knowledge graph for companion planting, climate suitability, and landscape design recommendations via natural language.

README

PlantOntology

PlantOntology

The world's first open-source plant knowledge graph — built by landscape professionals, for everyone.

Live Demo License: MIT Neo4j Python MCP Species

plantontology-production.up.railway.app

PlantOntology is an open-source knowledge graph that models plants, ecosystems, and landscape design relationships — making 19 years of professional landscape expertise available to everyone through AI.


🌍 Why PlantOntology?

Existing plant databases (iNaturalist, GBIF, Plants.com) store facts — scientific names, photos, basic traits.

PlantOntology stores relationships and intelligence:

수종 ──[동반식재]──▶ 수종          # Companion planting
수종 ──[기피관계]──▶ 수종          # Allelopathy / conflict
수종 ──[기후적합]──▶ 기후존        # Climate zone match
수종 ──[유지관리]──▶ 난이도        # Maintenance complexity
수종 ──[생태역할]──▶ 조류/곤충     # Ecological function
수종 ──[병해충]───▶ 방제법         # Pest/disease management
포장 ──[심미조합]──▶ 수종군        # Aesthetic combinations
토양 ──[적합수종]──▶ 수종          # Soil-species match

This powers questions like:

  • "느티나무 옆에 뭘 심으면 좋을까?" → companion planting recommendations
  • "서울 기후에서 자생종으로 공원 식재 계획 짜줘" → AI-generated planting plans
  • "이 배치가 생태적으로 건강한가?" → ecosystem health scoring
  • "드라이가든용 내건성 수종 20종 추천" → climate-adaptive selection

🎯 Who is this for?

User Use Case
🏡 Home gardeners "What should I plant next to my roses?"
🌇 Urban planners Green infrastructure optimization
🏗️ Landscape architects Design automation & spec generation
🌍 Climate adaptation orgs Drought-resistant, carbon-sequestering planting
🤖 AI developers Training data for AEC/landscape AI models
🎓 Students Open educational resource for landscape programs

🗂️ Project Structure

PlantOntology/
├── data/
│   ├── species/           ← Plant species JSON (Korean + global)
│   ├── relationships/     ← Companion, conflict, ecological edges
│   ├── climate_zones/     ← Korean climate zones (쾨펜 분류)
│   └── regulations/       ← 도시공원법, 건축법 조경 기준
├── ontology/
│   ├── schema.cypher      ← Neo4j node/relationship schema
│   └── constraints.cypher ← Unique constraints & indexes
├── api/
│   ├── main.py            ← FastAPI app
│   └── routers/           ← /species, /recommend, /plan, /ecosystem
├── sdk/
│   └── plantontology/     ← Python SDK (pip install plantontology)
├── mcp/
│   └── server.py          ← MCP server for Claude Code integration
└── scripts/
    ├── seed_neo4j.py      ← Load initial dataset into Neo4j
    └── import_gbif.py     ← Import from GBIF open data

🚀 Quick Start

git clone https://github.com/alexai-mcp/PlantOntology
cd PlantOntology
pip install -e ".[dev]"

# Start Neo4j (Docker)
docker run -p 7474:7474 -p 7687:7687 neo4j:latest

# Seed initial dataset
python scripts/seed_neo4j.py

# Start API
uvicorn api.main:app --reload

Use as MCP Server (Claude Code)

{
  "mcpServers": {
    "plantontology": {
      "command": "python",
      "args": ["-m", "mcp.server"],
      "cwd": "/path/to/PlantOntology"
    }
  }
}

📚 Documentation


🌱 Initial Dataset (Korean Native + Ornamental)

Phase 1: 500 species with full relationship data

  • 한국 자생 수종 200종 (Korean native trees/shrubs)
  • 조경 활용 교목/관목 200종 (Common landscape species)
  • 지피식물/초화류 100종 (Ground covers & perennials)

Each species includes:

  • 학명 / 국명 / 영명
  • 생육 특성 (수고, 수폭, 생장속도)
  • 기후 적합성 (한국 기후존 1–7)
  • 토양 적합성
  • 유지관리 난이도
  • 동반식재 / 기피 관계
  • 생태 기능 (탄소흡수, 조류유인, 밀원)
  • 조경 활용처 (가로수, 공원, 정원, 옥상녹화)

🗺️ Roadmap

Phase Milestone ETA
v0.1 한국 자생 수종 200종 + Neo4j 스키마 2026-04
v0.2 FastAPI + 추천 엔진 MVP 2026-05
v0.3 MCP 서버 + Claude Code 통합 2026-05
v0.4 글로벌 수종 확장 (아시아 1,000종) 2026-06
v1.0 기후 적응 식재 계획 자동 생성 2026-Q3

🤝 Contributing

PlantOntology thrives on contributions from:

  • Landscape architects — domain knowledge, species data
  • Botanists — ecological relationships, taxonomy
  • AI engineers — Graph RAG, recommendation algorithms
  • Translators — Korean ↔ English ↔ Japanese species data
  • Gardeners — real-world companion planting observations

See CONTRIBUTING.md for guidelines.


📄 License

MIT — free to use, modify, and distribute.


Built with 19 years of landscape expertise + AI by AlexLee Powered by Neo4j · FastAPI · Claude Code MCP

from github.com/AlexAI-MCP/PlantOntology

Установка PlantOntology

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/AlexAI-MCP/PlantOntology

FAQ

PlantOntology MCP бесплатный?

Да, PlantOntology MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для PlantOntology?

Нет, PlantOntology работает без API-ключей и переменных окружения.

PlantOntology — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить PlantOntology в Claude Desktop, Claude Code или Cursor?

Открой PlantOntology на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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