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  1. Home
  2. 🧠 Knowledge & Memory
  3. Owl MCP
Owl MCP logo
Health: ActiveRecent health check succeeded.Last checked 9/9/2026, 8:32:09 PM

Owl MCP

User RatingsBe the first to rate and review this MCP server!
View Repository3 GitHub StarsTotal stargazers on GitHub for the source repository (3 stars).Visit Website
owlrdfsparqlknowledge-graphsreasoning

MCP server for querying, editing, saving, and reasoning over OWL, TTL, and RDF ontologies.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "liftkkkk-owl-mcp": {
      "command": "uvx",
      "args": [
        "mcp"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives🧠 More in Knowledge & Memory

Overview

This server lets MCP clients load local ontology files or IRIs, inspect classes and individuals, run SPARQL 1.1 queries, and make selected changes. It supports Pellet and HermiT reasoning for consistency checks and inferred knowledge. Use it when an AI assistant needs to explore or update OWL-based knowledge graphs through natural language.

Use cases

•Explore ontology classes, properties, namespaces, and individuals
•Run SPARQL queries against loaded knowledge graphs
•Add classes, individuals, and object property assertions
•Check ontology consistency with Pellet or HermiT
•Save ontology changes as RDF/XML, Turtle, or N-Triples

Key features

•Load TTL, OWL, and RDF files or IRIs
•Inspect ontology structure and entity details
•Execute SPARQL 1.1 SELECT queries
•Create classes, individuals, and object property assertions
•Run Pellet or HermiT reasoning
•Save ontologies in multiple RDF formats

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Owl MCP.

Extracted Tool Capabilities
Load TTL, OWL, and RDF files or IRIs
Inspect ontology structure and entity details
Execute SPARQL 1.1 SELECT queries
Create classes, individuals, and object property assertions
Run Pellet or HermiT reasoning
Save ontologies in multiple RDF formats

Documentation Overview

🦉 OWL MCP Server

让 AI 直接读写你的 OWL / TTL / RDF 本体文件

License: MIT Python MCP owlready2

English · 快速开始 · 工具列表 · 示例


简介

OWL MCP Server 是一个基于 Model Context Protocol (MCP) 的本体操作服务器。

它让 Claude、Cursor、WorkBuddy 等 AI 助手能够像操作普通文件一样,直接查询、修改、推理你的 OWL/TTL/RDF 本体文件 —— 无需手写 SPARQL,无需了解 OWL 语法细节,用自然语言对话即可完成复杂的知识图谱操作。

Code
你:"找出所有 XX 类的个体,按金额降序排列"
AI:[调用 sparql_query] → 返回结构化结果

适用场景

  • 🏦 金融领域:对账单、票据本体的增删改查
  • 🏥 医疗健康:临床知识图谱探索与推理
  • 🏗️ 工程建模:设备、流程本体的管理与验证
  • 🎓 学术研究:OWL 本体的快速原型开发与测试

快速开始

第一步:安装依赖

Terminal
pip install mcp owlready2 rdflib

或使用 requirements.txt:

Terminal
pip install -r requirements.txt

⚠️ 推理器依赖 Java:使用 run_reasoner(Pellet/HermiT)需要本地安装 JDK 8+

第二步:配置 MCP 客户端

WorkBuddy

在 ~/.workbuddy/mcp.json 中添加:

config.json
{
  "mcpServers": {
    "owl": {
      "command": "python",
      "args": ["/绝对路径/server.py"]
    }
  }
}

💡 推荐:使用虚拟环境的 Python 绝对路径,避免依赖冲突:

json
"command": "C:/Users/yourname/.workbuddy/binaries/python/envs/default/Scripts/python.exe"

Claude Desktop

在 claude_desktop_config.json 中添加:

config.json
{
  "mcpServers": {
    "owl-mcp": {
      "command": "python",
      "args": ["/绝对路径/server.py"]
    }
  }
}

Cursor

在 .cursor/mcp.json 中添加同样的配置,重启 Cursor 后即可在 Agent 模式中使用。

第三步:启用并开始对话

在 WorkBuddy 连接器管理页面找到 owl,点击 Trust 启用,然后直接开始自然语言对话:

Code
"加载本体文件 C:/work/xxxx.ttl"
"列出所有类,只显示以 xxx: 开头的"
"描述 BankStatement 类的完整结构"
"运行 HermiT 推理器,检查本体一致性"
"把新增的类保存回原文件"

工具列表

📖 查询类

工具说明
load_ontology加载本体文件(支持本地路径或 IRI,格式:TTL / OWL / RDF)
get_ontology_info获取本体概览(类数、个体数、属性数、命名空间)
list_classes列出所有类,支持前缀过滤与数量限制
list_individuals列出所有个体,支持按类过滤
list_properties列出对象属性 / 数据属性
describe_class详细描述类(父类、子类、限制、已知个体)
describe_individual描述个体(所属类型、全部属性值)
search_entity按关键词模糊搜索类 / 个体 / 属性
sparql_query执行 SPARQL 1.1 SELECT 查询

✏️ 修改类

工具说明
add_class添加新类(可指定父类、rdfs:label、rdfs:comment)
add_individual添加新个体(可指定初始属性值)
add_object_property_assertion添加对象属性三元组断言
save_ontology保存本体(支持 rdfxml / turtle / ntriples)

🧠 推理类

工具说明
run_reasoner运行推理器(Pellet 或 HermiT),检查一致性并推断隐含知识

注意:add_* 系列修改操作不会自动保存,需显式调用 save_ontology。


示例用法

探索本体结构

Code
你:加载 xxx.ttl,给我一个整体介绍
AI:该本体共有 47 个类、213 个个体、18 个对象属性……

你:描述一下 BankStatement 类
AI:BankStatement 是 FinancialDocument 的子类,拥有以下数据属性:amount、currency、date……

SPARQL 查询

sparql
-- 查找所有 BankStatement 及其金额(降序)
PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX : <http://test.com/t#>

SELECT ?ind ?amount WHERE {
  ?ind rdf:type :BankStatement .
  ?ind :amount ?amount .
}
ORDER BY DESC(?amount)

增量修改

Code
你:新增一个 AA 类,父类是 BB,标签为"CC"
AI:[调用 add_class] → 已添加 AA 类

你:把这个改动保存为 turtle 格式
AI:[调用 save_ontology] → 已保存到 xxx.ttl

一致性检查

Code
你:运行 HermiT 推理器,检查本体有没有逻辑矛盾
AI:[调用 run_reasoner] → 本体一致,推断出 3 个新的隐含类成员关系……

技术栈

组件用途
owlready2OWL 本体加载、修改、推理器调用
rdflibSPARQL 1.1 查询引擎
mcpModel Context Protocol SDK

注意事项

  • 推理器需要 Java:Pellet / HermiT 依赖 JDK 8+,请确保 java 在系统 PATH 中
  • 大型本体:超过 10 万三元组时,list_* 系列操作请配合 limit 参数使用
  • 修改不自动保存:所有 add_* 操作仅更新内存模型,需手动调用 save_ontology
  • SPARQL 语法:使用标准 SPARQL 1.1 语法,由 rdflib 引擎执行

兼容的 MCP 客户端

  • ✅ WorkBuddy
  • ✅ Trae/Traw-work
  • ✅ Claude
  • ✅ Cursor (Agent 模式)
  • ✅ 任何支持 MCP 标准的 AI 客户端

License

MIT


☕ 请作者喝杯咖啡

OWL MCP Server 是我在业余时间独立开发和维护的开源项目,永久免费。

如果它帮你省下了哪怕半小时手写 SPARQL 的时间,可以考虑请我喝杯咖啡(¥9.9 就够 ☕)—— 你的每一份支持都会直接转化为新功能开发和 bug 修复的动力。

赞赏码 - 请作者喝咖啡

扫码赞赏时可以留言你最想要的功能,我会优先安排 😉

不方便赞赏? 给项目点个 ⭐ Star、提一个 Issue、或把它分享给需要的人,同样是巨大的支持!


Read the full README →View source on GitHub →

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars
3
Stargazers on the source repository.
npm downloads
6k
Package downloads in the last 30 days.
Last commit
2mo ago
Most recent push to the default branch.
Directory activity
1 views
Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Owl MCP

It supports TTL, OWL, and RDF ontology files, as well as ontology IRIs.

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Technical Specs & Signals

Category🧠Knowledge & Memory
PricingFree
More technical detailsExpand ▾
TransportSTDIO
RuntimePython
AuthNo auth required
LicenseMIT
ClientsClaude Desktop, Cursor, Windsurf
Last updatedAug 9, 2026
10/10 checks healthy over the last 31d
Views1
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars3
GitHub Star CountTotal stargazers on GitHub representing community popularity (3 stars).
Last commit2mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Jul 11, 2026
npm downloads6,013/mo
Monthly npm DownloadsAverage monthly package installs recorded from npm registry statistics.
45Quality signal: Fair · 45/100How this signal is calculated ▾
Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership4/20
Documentation & tools23/30
Adoption & activity7/15
Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

6 high-severity advisories on record for this package. Most advisories affect transitive dependencies and may not be exploitable in this server's actual usage — this is a directional signal, not a security audit.

Critical 0High 6Medium 0Low 6

Scanned 27d ago via OSV.dev · mcp (PyPI)

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