StreamsHub MCP
StreamsHub MCP provides Model Context Protocol (MCP) servers that give AI assistants direct access to Kubernetes-based streaming infrastructure. Each component of your streaming stack gets its own MCP server that can be deployed independently.
Works with any MCP-compatible client including Claude Code, Claude Desktop, VS Code, Copilot, and more.
MCP servers
Key capabilities
StreamsHub MCP servers leverage the full MCP specification:
- Prompt templates -- Structured diagnostic workflows that guide the LLM step-by-step through complex troubleshooting
- Resource templates -- Live cluster state exposed as structured context that clients can attach directly to conversations
- Resource subscriptions -- Kubernetes watches that push real-time notifications when cluster state changes
- Completions -- Dynamic autocomplete for parameters (namespaces, cluster names, topics) powered by live Kubernetes queries
- Progress and cancellation -- Long-running operations report progress and support mid-operation cancellation
Getting started
Pick a server from the table above and follow its getting started guide.
For the full documentation, see the documentation/ directory (modular AsciiDoc).
Build it to HTML locally with ./mvnw -N -Pdocs package (output in target/documentation/).
Development
./mvnw compile # Compile all modules (includes checkstyle)
./mvnw test # Run unit tests
./mvnw verify -Psystemtest # Run system tests (requires Kubernetes cluster)
For more details:
- Contributing -- Contribution workflow and guidelines
- Testing -- Unit and system test guide
Built with
- Quarkus -- Cloud-native Java framework
- Fabric8 Kubernetes Client -- Kubernetes API access
- Quarkus MCP Server -- MCP protocol implementation
