Huashu Design
alchaincyf · Skill
Turns a one-line request in your AI agent into a finished design: a launch animation, a clickable app prototype, an editable slide deck, an infographic or a se…
New29.4k
Overview
Builds and manages semantic, graph-based knowledge layers from enterprise metadata to ensure reliable AI agent interactions. It features automated schema discovery, natural language query generation, and support for the Model Context Protocol.
Auto Ontology is an open-source project on GitHub in the Developer category, listed by Mindket. It is free. This is version 1, last updated on . Install it from GitHub as its README says. Get Mindket’s setup notes on your Mindket account, as a zip.
At a glance
- Start with
docker compose up -d --build
Platform
Server
About
What it is
Auto Ontology is a library that builds a semantic layer from enterprise metadata to provide agents with trusted business meaning. It generates ontologies, reconciles definitions across systems, and exposes these to agents through MCP, CLI, and API.
Who it suits
It is designed for developers who need to ground their agents in certified business logic and metadata.
Where to use it
This tool functions through a web interface, CLI, REST API, or as an MCP server.
How to set it up
You need Docker with Compose v2, the uv package manager, and an NVIDIA API key from the NVIDIA API catalog.
- Clone the repository and create your .env file.
- Set your API key and internal passwords in the .env file.
- Start the database service and run the seed script to load sample data.
- Build and launch the stack using Docker Compose.
- Open the web interface, sign in, and enable semantic compilation in the settings.
docker compose up -d --build
How to use it
You interact with the system by asking questions in the web chat, through the REST API, or by using MCP tools in compatible agents.
Example
The agent returns the answer, the generated SQL code, and the steps it took to reach that result.
For newcomers and experts
For those new to this, the system acts as a bridge that teaches your AI company-specific terms and data relationships. Experts can use the system to build knowledge graphs, validate generated queries against certified definitions, and expose these through an agent harness.
Good to know
- Supports ten database engines including PostgreSQL, MySQL, Databricks, and Snowflake.
- Requires configuration of separate model roles for reasoning, entity extraction, and embeddings.
- Does not accept external code contributions.
- License: Apache License 2.0.
README and files
Auto Ontology
Builds and manages semantic, graph-based knowledge layers from enterprise metadata to ensure reliable AI agent interactions. It features automated schema discovery, natural language query generation, and support for the Model Context Protocol.
Made by NVIDIA on GitHub. These notes are Minda's, written from its README; the project's own files and license are in its repository.
About
What it is: Auto Ontology is a library that builds a semantic layer from enterprise metadata to provide agents with trusted business meaning. It generates ontologies, reconciles definitions across systems, and exposes these to agents through MCP, CLI, and API.
Who it suits: It is designed for developers who need to ground their agents in certified business logic and metadata.
Where to use it: This tool functions through a web interface, CLI, REST API, or as an MCP server.
How to set it up: You need Docker with Compose v2, the uv package manager, and an NVIDIA API key from the NVIDIA API catalog.
- Clone the repository and create your .env file.
- Set your API key and internal passwords in the .env file.
- Start the database service and run the seed script to load sample data.
- Build and launch the stack using Docker Compose.
- Open the web interface, sign in, and enable semantic compilation in the settings.
docker compose up -d --buildHow to use it: You interact with the system by asking questions in the web chat, through the REST API, or by using MCP tools in compatible agents.
Example: The agent returns the answer, the generated SQL code, and the steps it took to reach that result.
For newcomers and experts: For those new to this, the system acts as a bridge that teaches your AI company-specific terms and data relationships. Experts can use the system to build knowledge graphs, validate generated queries against certified definitions, and expose these through an agent harness.
Good to know:
- Supports ten database engines including PostgreSQL, MySQL, Databricks, and Snowflake.
- Requires configuration of separate model roles for reasoning, entity extraction, and embeddings.
- Does not accept external code contributions.
- License: Apache License 2.0.
On GitHub, 5 November 2026
- Stars: 5,165 (2,050 that day)
- Forks: 409
- Watching: 31
- Open issues and pull requests: 42
- Language: Python
- License: Apache-2.0
- Trending: #1 repository of the day on GitHub trending (5 November 2026)
Links
- Code: https://github.com/NVIDIA/auto-ontology
- Releases: https://github.com/NVIDIA/auto-ontology/releases
- Issues: https://github.com/NVIDIA/auto-ontology/issues
- Star history: https://www.star-history.com/#NVIDIA/auto-ontology&Date
Intro videos
- auto-ontology — NVIDIAのスキーマ意味層ビルダー｜GitHub Trending TOP5 11/5: https://www.youtube.com/watch?v=faJh1Sstx8s
- NVIDIA/auto-ontology - Auto Ontology es un framework de Python para crear capas de razonamiento…: https://www.youtube.com/watch?v=zl7G2s1mWAI
- Instant Apache Ossie Model Generation | Auto-Ontology Feature Demo: https://www.youtube.com/watch?v=mG4YcQZ_UII
Get the code
git clone https://github.com/NVIDIA/auto-ontology.gitThen follow the setup in its README. Nothing in this kit runs by itself.
README.md 3 KB
What’s new
Reviews
What people say
Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search and on Trendshift. Mindket doesn’t write or check them. Open one to read it where it was posted.
campervansNvidia – open-source auto-ontology291 points · 139 repliesEdy | Indie BuilderToday's GitHub trending: reusable skills for coding agents - cloudflare/security-audit-skill: phased audits (+2,548 today) - NVIDIA/auto-ontology: semantic graph for agents (+2,015) - google/skills: Google tech agent skills (+534) github.com/cloudflare/s... #buildinpublic #AI5 likes · 1 reply@AIFactAuditAi Fact Audit on X: "NVIDIA open-sourced Auto Ontology, trending on ...NVIDIA open-sourced Auto Ontology, trending on GitHub (4,548 stars, verified via GitHub API). It gives AI agents a semantic/graph layer for grounded, provenance-checked answers over enterprise data. Apache-2.0. GitHub - NVIDIA/auto-ontology: Auto Ontology is a Python framework for building…marcfox182Nvidia Auto Ontology lidera GitHub Trending e amplia propostas2 pointsGitHub Trending💎 Hidden Gem！ 💎 (1000+ new stars) 📦 NVIDIA / auto-ontology ⭐ 3,666 (+2,053) 🗒 Python Auto Ontology is a Python framework for building semantic, graph-based reasoning layers over data. It enables deterministic query generation, better context retrieval, and more explainable AI for LLM...5 likes · 1 reply@panExorcist驱魔先生 ️ on X: "今天 GitHub 日榜又燃爆了! 帮你省下刷榜时间，直接拿 5 个能用的工具 1️⃣ NVIDIA/auto ...今天 GitHub 日榜又燃爆了! 🔥 帮你省下刷榜时间，直接拿 5 个能用的工具👇 1️⃣ NVIDIA/auto-ontology ⭐ 3,675 Stars｜今日 +2,053｜Python 是什么：语义图推理层，让 LLM / Agent 的查询生成更确定、过程更可解释。 适合：做 RAG、企业知识库的开发者。trustbutverafyNvidia Auto Ontology, but a Graph1 point · 1 replyRobert Corbin | Shadowfetch Studio | AIpeoplewikiNVIDIA open-sourced Auto Ontology under Apache 2.0 🧩 It builds a semantic layer from enterprise metadata so AI agents write SQL against trusted business definitions, served over MCP, CLI and API. #AI #AIAgents #OpenSource github.com/NVIDIA/auto-...4 likesmatthieu_blShow HN: Alternative to Nvidia Auto-OntologyThis repo provides an alternative to the ontology compiling capabilities of NVIDA Auto-Ontology. The main difference is that it builds the ontology from most of your existing data assets (transformation code, dashboards, docs), instead of building it from your warehouse and semantic layer only. It…1 point@qdrddr.bsky.socialBuild ontologies with #LLM, #Embeddings, #Reranking with Nvidia Auto #Ontology #OpenSource Apache 2.0 #KnowledgeGraph #RDF github.com/NVIDIA/auto-...2 likes · 1 replytrustbutverafyNvidia Auto Ontology, but a GraphNvidia Auto Ontology makes a beautiful ontology in Neo4j, a mediocre graph database, and puts it inside Postgres, not a graph database at all. Nidra Computer bravely asks: what if we just used a graph database for this, folks? The semantic web lives on!@ai-trend-to-know.bsky.socialNVIDIA/auto-ontology 💻 Python #SoftwareArchitecture #Python #OpenSource #AIAgents 🔗 trendtoknow.com/NVIDIA/auto-...2 likes
More from Mindket
See all from MindketGuizang PPT Skill
op7418 · Skill
Skill that makes single-file HTML slide decks, slide illustrations and platform covers in two visual styles, with a presenter mode for rehearsal. For speakers…
New29.8k
Claude Code Skills & Plugins
alirezarezvani · Skill
Adds 411 ready-made skills for Claude Code and other coding agents, grouped by role from engineering and product to marketing, finance and compliance. Installs…
New29.8k
Similar in Developer
See all in Developerbuzz
block · Kit
Self-hostable workspace where people and AI agents share the same rooms, built on a Nostr relay that logs every action as a signed event. For teams that want t…
New37.3k
plannotator
backnotprop · Kit
Opens your AI coding agent's plans, specs and code changes in a browser so you can annotate or comment on them and send the feedback straight back to the agent.
New10.5k
open-code-review
alibaba · Kit
Reviews Git changes with an AI agent that reads files and searches the codebase, then writes comments tied to exact lines. It suits developers who want automat…
New50.7k