✦ Context Ontology Accelerator

An open-source semantic context layer for AWS that combines knowledge graphs, formal ontologies, and rule-based systems with modern AI — enabling agents to retrieve context, validate it against business logic, and determine correct actions.

Architecture

The system follows a Scan → Model → Serve workflow:

• Scan — Connect data sources, discover schemas, enrich metadata, ingest unstructured documents
• Model — Induce and manage ontologies, define metrics, build a unified semantic graph
• Serve — Query via SPARQL federation (VKG), traverse the knowledge graph, serve context to AI agents via MCP

Quick Start

Prerequisites

• Python 3.12, Node.js 22.23.4+, Docker
• pnpm (Node package manager — installed via mise or npm install -g pnpm)
• Java 17–24 (21 recommended) and Gradle (for Smithy codegen), plus Maven (for the

• uv (Python package manager)

Setup

Use a release, not the tip of main. We recommend starting from a tagged

release — github.com/aws/context-ontology-accelerator/releases.

main tracks ongoing development.

# Clone at the latest release tag (replace <tag> with a release from the link above)
git clone --branch <tag> https://github.com/aws/context-ontology-accelerator.git
cd context-ontology-accelerator
make setup      # install Python + CDK TypeScript dependencies
make format     # auto-format code
make lint       # check linting
make test       # run unit tests

Full developer guide: external-docs/content/getting-started.md

Repository Structure

semantic-context/
├── models/              # Smithy API models (source of truth for API contracts)
├── smithy-generated/    # Auto-generated from Smithy (OpenAPI, Python interfaces, TS client)
├── infra/               # AWS CDK (TypeScript) — foundation + per-service stacks
├── packages/
│   ├── control-plane/           # Control Plane APIs
│   ├── data-layer/              # Data Layer APIs (query, retrieval, traversal)
│   ├── sources/                 # Unified data source ingestion (database + documents)
│   ├── ontology-engine/         # Ontology induction, reasoning (HermiT/ELK)
│   ├── metric-service/          # Metric authoring and resolution
│   ├── vkg/                     # Virtual Knowledge Graph (Ontop)
│   ├── mcp-server/              # MCP tools for AI agents
│   ├── context-manager/         # Serve layer Context Manager (query orchestration, upstream clients)
│   └── web-app/                 # React + Cloudscape frontend
├── libs/common/         # Shared Python config, logging, exceptions
├── libs/ts-shared/      # Shared TypeScript interfaces and constants
├── connectors/          # Athena federation connectors: toolkit, reference connector, Databricks
├── coa-skills/          # Agent skills for driving a deployed COA (control-plane)
├── scripts/             # CI-agnostic build/test/deploy scripts
└── external-docs/       # Published documentation (getting-started, deployment guides)

Tech Stack

| Layer | Technology | | ---------------------- | -------------------------------------------------------- | | Languages | Python 3.12, TypeScript | | API Contracts | Smithy → OpenAPI + Python interfaces + TypeScript client | | IaC | AWS CDK (TypeScript) | | Frontend | React + Cloudscape Design System | | Package Management | uv (Python), pnpm (TypeScript) | | Monorepo Orchestration | Nx | | Testing | pytest (unit + integ) | | Linting | ruff, mypy (strict) | | Codegen | Smithy CLI (Java 17 + Gradle) |

Contributing

This repository is published as a read-only mirror. We are not accepting pull requests at this time. You are welcome to report bugs and share feedback through GitHub Issues. See CONTRIBUTING.md for details including direction for Amazon employees.

External Dependencies

This package depends on and may incorporate or retrieve a number of third-party software packages (such as open source packages) at install-time or build-time or run-time ("External Dependencies"). The External Dependencies are subject to license terms that you must accept in order to use this package. If you do not accept all of the applicable license terms, you should not use this package. We recommend that you consult your company’s open source approval policy before proceeding.

Provided below is a list of External Dependencies and the applicable license identification as indicated by the documentation associated with the External Dependencies as of Amazon's most recent review.

THIS INFORMATION IS PROVIDED FOR CONVENIENCE ONLY. AMAZON DOES NOT PROMISE THAT THE LIST OR THE APPLICABLE TERMS AND CONDITIONS ARE COMPLETE, ACCURATE, OR UP-TO-DATE, AND AMAZON WILL HAVE NO LIABILITY FOR ANY INACCURACIES. YOU SHOULD CONSULT THE DOWNLOAD SITES FOR THE EXTERNAL DEPENDENCIES FOR THE MOST COMPLETE AND UP-TO-DATE LICENSING INFORMATION.

YOUR USE OF THE EXTERNAL DEPENDENCIES IS AT YOUR SOLE RISK. IN NO EVENT WILL AMAZON BE LIABLE FOR ANY DAMAGES, INCLUDING WITHOUT LIMITATION ANY DIRECT, INDIRECT, CONSEQUENTIAL, SPECIAL, INCIDENTAL, OR PUNITIVE DAMAGES (INCLUDING FOR ANY LOSS OF GOODWILL, BUSINESS INTERRUPTION, LOST PROFITS OR DATA, OR COMPUTER FAILURE OR MALFUNCTION) ARISING FROM OR RELATING TO THE EXTERNAL DEPENDENCIES, HOWEVER CAUSED AND REGARDLESS OF THE THEORY OF LIABILITY, EVEN IF AMAZON HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. THESE LIMITATIONS AND DISCLAIMERS APPLY EXCEPT TO THE EXTENT PROHIBITED BY APPLICABLE LAW.

| External Dependency | License | Source | | ------------------- | ------- | ------ | | owlready2 | LGPL-3.0 | https://pypi.org/project/owlready2/ |

License

This project is licensed under the Apache License 2.0 — see LICENSE for details.