giantswarm/muster

Muster: Universal Control Plane for AI Agents

In German, Muster means "pattern" or "sample." This project provides the building blocks for AI agents to discover patterns and collect samples from any digital environment. It gives them a universal protocol to interact with the world.

Muster is a universal control plane built on the Model Context Protocol (MCP) that solves the MCP server management problem for platform engineers and AI agents.

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The Platform Engineer's Dilemma

As a platform engineer, you interact with countless services: Kubernetes, Prometheus, Grafana, Flux, ArgoCD, cloud providers, and custom tooling. While tools like Terraform and Kubernetes operators provide unified orchestration interfaces, debugging and monitoring still requires jumping between different tools and contexts.

The MCP Revolution: LLM agents (in VSCode, Cursor, etc.) + MCP servers should solve this by giving agents direct access to your tools. There are already many excellent MCP servers available (Kubernetes, Prometheus, Grafana, Flux, etc.).

But there's a problem:

• Adding all MCP servers to your agent pollutes the context and increases costs
• Turning servers on/off manually is tedious and error-prone
• Tool discovery becomes overwhelming as your toolkit grows
• No coordination between different MCP servers and their prerequisites

The Solution: Intelligent MCP Aggregation

Muster solves this by creating a meta-MCP server that manages all your MCP servers and provides your agent with intelligent tool discovery capabilities.

📖 Learn More: MCP Aggregation Deep Dive | [System Architecture](docs/explanation/archite