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Glama

Server Details

The Google GKE MCP server is a managed Model Context Protocol server that provides AI applications with tools to manage Google Kubernetes Engine (GKE) clusters and Kubernetes resources. It exposes a structured, discoverable interface that allows AI agents to interact with GKE and Kubernetes APIs, enabling them to inspect cluster configurations, retrieve Kubernetes resource YAMLs, monitor operations like cluster upgrades, diagnose issues, and optimize costs—all without needing to parse text output or use complex kubectl commands.

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL

Glama MCP Gateway

Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.

MCP client
Glama
MCP server

Full call logging

Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.

Tool access control

Enable or disable individual tools per connector, so you decide what your agents can and cannot do.

Managed credentials

Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.

Usage analytics

See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.

100% free. Your data is private.
Tool DescriptionsA

Average 3.7/5 across 23 of 23 tools scored.

Server CoherenceA
Disambiguation5/5

Every tool has a clearly distinct purpose targeting specific GKE/Kubernetes resources and operations. The tools are well-differentiated by their target objects (clusters, node pools, Kubernetes resources, operations) and actions (create, get, list, update, delete, apply, patch, check, describe). There is no significant overlap that would cause confusion.

Naming Consistency5/5

The tool names follow a highly consistent verb_noun pattern throughout (e.g., create_cluster, get_cluster, list_clusters, update_cluster). All tools use snake_case with clear action prefixes (apply, cancel, check, create, delete, describe, get, list, patch, update) followed by specific resource names, making the naming scheme predictable and readable.

Tool Count4/5

With 23 tools, the count is on the higher side but reasonable for the broad scope of GKE cluster and Kubernetes resource management. It covers cluster operations, node pool management, and comprehensive Kubernetes interactions, though it might feel slightly heavy compared to more focused servers.

Completeness5/5

The toolset provides complete CRUD/lifecycle coverage for GKE clusters, node pools, and Kubernetes resources. It includes creation, retrieval, listing, updating, deletion, patching, and status checking operations, along with auxiliary functions like authentication checks, logging, and event monitoring. There are no obvious gaps for the stated domain.

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