InfraGenius

InfraGenius is an AI-powered DevOps and SRE intelligence platform designed to assist with infrastructure reliability, scalable architecture decisions, and operational automation. As an MCP server, it exposes a RESTful API and CLI tooling that enable automated reasoning, model-driven recommendations, and actionable automation flows across your stack. The platform emphasizes local development compatibility (via Ollama/Open-source models) and integration with common DevOps tools to help teams diagnose incidents, optimize deployments, and codify best practices. Expected usage includes querying infrastructure health, requesting optimization suggestions, and generating runbooks or automation scripts based on your environment.

To interact with InfraGenius, you would typically start the MCP server and use its provided endpoints or CLI to submit tasks, retrieve AI-assisted guidance, and orchestrate responses into your pipelines or dashboards. The server is designed to work in Kubernetes or Docker-based environments, and aims to provide sub-second responses through smart caching and a streamlined AI inference path.

Prerequisites:

• Docker and Docker Compose (recommended for local and containerized setups)
• Git (for cloning the repository or pulling the container image)
• Optionally Ollama if you want to leverage local open-source models for development

Option A: Run InfraGenius via Docker (recommended for quick start)

1. Install Docker: follow instructions at https://docs.docker.com/get-docker/
2. Pull and run the InfraGenius image:

# Start InfraGenius container (interactive)
docker run -it -p 8000:8000 --name infragenius infragenius/InfraGenius:latest

3. Verify the server is up:

curl http://localhost:8000/health

4. Use the REST API or CLI as documented by the project (endpoints typically include health, docs, and inference routes).

Option B: Run locally from source (if repository provides a local dev setup)

1. Clone the repository:

git clone https://github.com/infragenius/infragenius.git
cd infragenius

2. Install dependencies (language-specific, see repository docs):

# example for a Node.js/Python-based server (adjust as needed)
npm install   # or pip install -r requirements.txt

3. Start the server in development mode (see docs for exact command):

# example placeholder
npm run dev   # or uvx run server.py / python -m infragenius

4. Open the UI/docs and begin issuing requests to the local API at http://localhost:8000

Notes and tips:

• If you intend to run locally with Ollama, ensure Ollama is installed and the Ollama service is running before starting InfraGenius.
• When deploying in Kubernetes, wire InfraGenius behind an API gateway and enable authentication and rate limiting as shown in the architecture diagram.
• Environment variables and configuration options are typically surfaced in a config file or via container environment variables; look for variables like MODEL_PATH, DB_CONNECTION, API_KEYS, and CACHE_SIZE in the project docs.
• If you encounter port conflicts, adjust the host port mapping in your docker/run command or Kubernetes service to avoid clashes with existing services.
• Check the monitoring stack (Prometheus/Grafana/Jaeger) for health and performance metrics to diagnose latency or cache misses.