opendatahub-io/rhoai-mcp

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Repository Install

Prototype MCP server for RHOAI

Обзор

An MCP (Model Context Protocol) server that enables AI agents to interact with Red Hat OpenShift AI (RHOAI) environments. This server replicates the capabilities of the OpenShift AI Dashboard through programmatic tools. - : Create, list, and manage Data Science Projects - : Create, start, stop, and delete Jupyter workbenches - : Deploy and manage InferenceServices with KServe - : Manage S3 credentials for data access - : Configure Data Science Pipelines infrastructure - : Create and manage persistent volume claims - : Fine-tune models with Kubeflow Training Operator - : Workflow guidance for multi-step operations (18 prompts) Want to add your team's capabilities to rhoai-mcp? See the contributor guide for templates, documentation, and a working example domain. For OpenShift installation, refer to OpenShift deployment.

README

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RHOAI MCP Server

Features

Project Management: Create, list, and manage Data Science Projects
Workbench Operations: Create, start, stop, and delete Jupyter workbenches
Model Serving: Deploy and manage InferenceServices with KServe
Data Connections: Manage S3 credentials for data access
Pipelines: Configure Data Science Pipelines infrastructure
Storage: Create and manage persistent volume claims
Training: Fine-tune models with Kubeflow Training Operator
MCP Prompts: Workflow guidance for multi-step operations (18 prompts)

Technology Stack

Component	Technology	Purpose
Runtime	Python 3.11+	Core language
MCP Framework	FastMCP 1.0+	Model Context Protocol server
Kubernetes Client	kubernetes-python 28.1+	Cluster API interactions
Data Validation	Pydantic 2.0+	Type-safe models and settings
HTTP Client	httpx 0.27+	Async HTTP requests
Container Base	Red Hat UBI 9	Production container image
Package Manager	uv	Fast Python dependency management

Extending

Want to add your team’s capabilities to rhoai-mcp? See the contributor guide for templates, documentation, and a working example domain.

Installation

For OpenShift installation, refer to OpenShift deployment.

Using uv (recommended)

# Clone the repository
git clone https://github.com/opendatahub-io/rhoai-mcp.git
cd rhoai-mcp

# Install dependencies
uv sync

# Run the server
uv run rhoai-mcp

Using pip

pip install -e .
rhoai-mcp

Using Container (Podman/Docker)

# Build the image
make build

Открыть полный README на GitHub

Установка

uvx --from git+https://github.com/opendatahub-io/rhoai-mcp rhoai-mcp

Новичок в MCP? Начните с руководства на mcpskill.org →

Конфигурация

{
  "mcpServers": {
    "rhoai-mcp": {
      "url": "https://<RHOAI_MCP_ROUTE>/mcp"
    }
  }
}