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liftkkkk/owl-mcp

liftkkkk/owl-mcp

Work with OWL/TTL/RDF ontologies: SPARQL queries,
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add owl-mcp -- npx -y owl-mcp
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
5 ★ · liftkkkk/owl-mcp · 取自该仓库的 GitHub 页面 · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
评分构成
综合分 703 · 5 ★ · 7 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 liftkkkk/owl-mcp;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

🦉 OWL MCP Server

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

**Let AI read and write your OWL / TTL / RDF ontology files directly**
**English** | 简体中文
Quick Start · Tools · Examples
---
Introduction
**OWL MCP Server** is an ontology manipulation server built on the Model Context Protocol (MCP).
It lets AI assistants such as Claude, Cursor, and WorkBuddy **query, modify, and reason over** your OWL/TTL/RDF ontology files as easily as ordinary files — no hand-written SPARQL, no OWL syntax details; complex knowledge-graph operations done through natural-language conversation.
Use Cases
- 🏦 **Finance**: CRUD on bank-statement and invoice ontologies
- 🏥 **Healthcare**: exploration and reasoning over clinical knowledge graphs
- 🏗️ **Engineering**: management and validation of equipment and process ontologies
- 🎓 **Research**: rapid prototyping and testing of OWL ontologies
---
Quick Start
Step 1: Install dependencies
Or via requirements.txt:
> ⚠️ **Reasoners need Java**: run_reasoner (Pellet/HermiT) requires a local **JDK 8+** installation.
Step 2: Configure your MCP client
WorkBuddy
Add to ~/.workbuddy/mcp.json:
> 💡 **Recommended**: use the absolute path of a virtualenv Python to avoid dependency conflicts:
>
Claude Desktop
Add to claude_desktop_config.json:
Cursor
Add the same configuration to .cursor/mcp.json, restart Cursor, and the server is available in Agent mode.
Step 3: Enable it and start talking
In the WorkBuddy connector management page, find owl, click **Trust** to enable it, then just chat in natural language:
---
Tools
📖 Query tools
| Tool | Description |
|------|-------------|
| load_ontology | Load an ontology file (local path or IRI; formats: TTL / OWL / RDF) |
| get_ontology_info | Get an overview (counts of classes, individuals, properties; namespaces) |
| list_classes | List all classes, with prefix filtering and limit |
| list_individuals | List all individuals, optionally filtered by class |
| list_properties | List object properties / data properties |
| describe_class | Describe a class in detail (parents, children, restrictions, known individuals) |
| describe_individual | Describe an individual (types and all property values) |
| search_entity | Fuzzy-search classes / individuals / properties by keyword |
| sparql_query | Run a SPARQL 1.1 SELECT query |
✏️ Modification tools
| Tool | Description |
|------|-------------|
| add_class | Add a new class (with optional parent, rdfs:label, rdfs:comment) |
| add_individual | Add a new individual (with optional initial property values) |
| add_object_property_assertion | Add an object-property triple assertion |
| save_ontology | Save the ontology (rdfxml / turtle / ntriples) |
🧠 Reasoning tools
| Tool | Description |
|------|-------------|
| run_reasoner | Run a reasoner (Pellet or HermiT) to check consistency and infer implicit knowledge |
> **Note**: add_* operations are not saved automatically — call save_ontology explicitly.
---
Examples
Exploring the ontology structure
来源
awesome · https://github.com/liftkkkk/owl-mcp
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