Gke (google Kubernetes Engine) Mcp

What is Gke (google Kubernetes Engine) Mcp?

Gke (google Kubernetes Engine) Mcp is an MCP server that enables AI‑compatible agents to interact with Google Kubernetes Engine. It provides tools and context instructions for managing clusters, reviewing costs, and checking known issues directly from an AI assistant.

How to use Gke (google Kubernetes Engine) Mcp?

Install the gke-mcp binary using the quick install script (curl -sSL https://raw.githubusercontent.com/GoogleCloudPlatform/gke-mcp/main/install.sh | bash) or manually with go install. Then add the server to your AI – for example, run gke-mcp install gemini-cli for Gemini CLI, or merge the JSON snippet into your MCP configuration for other AI tools.

Key features of Gke (google Kubernetes Engine) Mcp

• Creates AI‑optimized GKE clusters.
• Lists and retrieves detailed cluster information.
• Generates GKE manifests for AI/ML inference.
• Provides recommendations and queries GKE logs.
• Offers context on GKE costs and known issues.

Use cases of Gke (google Kubernetes Engine) Mcp

• AI agents provisioning and managing GKE clusters automatically.
• Troubleshooting by querying Google Cloud logs with Logging Query Language.
• Generating deployment manifests for AI inference workloads using Google Inference Quickstart.
• Checking a cluster’s impact from the latest GKE known issues.
• Getting cost‑related answers about clusters, namespaces, and Kubernetes workloads.

FAQ from Gke (google Kubernetes Engine) Mcp

Which AI agents can I use with this MCP server?

Gemini CLI is directly supported via the install gemini-cli command. Other AI tools that accept JSON‑based MCP configuration can also be used by adding the provided mcpServers snippet.

How do I install the server?

Two options: run the quick install script (Linux/macOS only) or install Go and then run go install github.com/GoogleCloudPlatform/gke-mcp@latest. The binary will be placed in your GOBIN directory.

What tools are included?

The server exposes tools for cluster creation, listing/getting clusters, generating AI inference manifests, listing recommendations, querying logs, and fetching log schemas.

Does the server offer any built‑in context beyond tools?

Yes – the server bundles context instructions that allow the AI to answer questions about GKE costs and to fetch and check the latest GKE known issues.

Are there any runtime requirements besides the binary?

No additional runtime is required after installation. The binary is self‑contained; no external services or dependencies need to be manually configured.