KubeAPI MCP Server and Gemini CLI Extension

Enable MCP-compatible AI agents to interact with Kubernetes.

Installation

Choose a way to install the MCP Server and then connect your AI to it.

Use as a Gemini CLI Extension

1. Install Gemini CLI.

2. Install the extension

gemini extensions install https://github.com/dmitryshnayder/kubeapi-mcp.git

Use in MCP Clients / Other AIs

Quick Install (Linux & macOS only)

curl -sSL https://raw.githubusercontent.com/dmitryshnayder/kubeapi-mcp/main/install.sh | bash

Manual Install

If you haven't already installed Go, follow these instructions.

Once Go is installed, run the following command to install kubeapi-mcp:

go install github.com/dmitryshnayder/kubeapi-mcp@latest

The kubeapi-mcp binary will be installed in the directory specified by the GOBIN environment variable. If GOBIN is not set, it defaults to $GOPATH/bin and, if GOPATH is also not set, it falls back to $HOME/go/bin.

You can find the exact location by running go env GOBIN. If the command returns an empty value, run go env GOPATH to find the installation directory.

For additional help, refer to the troubleshoot section: kubeapi-mcp: command not found.

Add the MCP Server to your AI

For detailed instructions on how to connect the KubeAPI MCP Server to various AI clients, including cursor and claude desktop, please refer to our dedicated installation guide.

MCP Tools

• kube_get_resource: Get a Kubernetes resource.
• kube_list_resources: List Kubernetes resources.
• kube_apply_resource: Apply a Kubernetes resource.
• kube_delete_resource: Delete a Kubernetes resource.

MCP Context

In addition to the tools above, a lot of value is provided through the bundled context instructions.

• Cost: The provided instructions allows the AI to answer many questions related to Kubernetes costs, including queries related to clusters, namespaces, and Kubernetes workloads.

• Kubernetes Known Issues: The provided instructions allows the AI to fetch the latest Kubernetes Known issues and check whether the cluster is affected by one of these known issues.

Supported MCP Transports

By default, kubeapi-mcp uses the stdio transport. Additionally, the Streamable HTTP transport is supported as well.

You can set the transport mode using the following options:

--server-mode: transport to use for the server: stdio (default) or http

--server-port: server port to use when server-mode is http or sse; defaults to 8080

kubeapi-mcp --server-mode http --server-port 8080

[!WARNING] When using the Streamable HTTP transport, the server listens on all network interfaces (e.g., 0.0.0.0), which can expose it to any network your machine is connected to. Please ensure you have a firewall ad/or other security measures in place to restrict access if the server is not intended to be public.

Connecting Gemini CLI to the HTTP Server

To connect Gemini CLI to the kubeapi-mcp HTTP server, you need to configure the CLI to point to the correct endpoint. You can do this by updating your ~/.gemini/settings.json file. For a basic setup without authentication, the file should look like this:

{
  "mcpServers": {
    "kubeapi": {
      "httpUrl": "http://127.0.0.1:8080/mcp"
    }
  }
}

This configuration tells Gemini CLI how to reach the kubeapi-mcp server running on your local machine at port 8080.

Development

To compile the binary and update the gemini-cli extension with your local changes, follow these steps:

1. Remove the global kubeapi-mcp configuration

   rm -rf ~/.gemini/extensions/kubeapi-mcp
   

2. Build the binary from the root of the project:

   go build -o kubeapi-mcp .
   

3. Run the installation command to update the extension manifest:

   ./kubeapi-mcp install gemini-cli --developer
   

   This will make gemini-cli use your locally compiled binary.