kubernetes-mcp-server

# MCP Prompts Support The Kubernetes MCP Server supports [MCP Prompts](https://modelcontextprotocol.io/docs/concepts/prompts), which provide pre-defined workflow templates and guidance to AI assistants. ## What are MCP Prompts? MCP Prompts are pre-defined templates that guide AI assistants through specific workflows. They combine: - **Structured guidance**: Step-by-step instructions for common tasks - **Parameterization**: Arguments that customize the prompt for specific contexts - **Conversation templates**: Pre-formatted messages that guide the interaction ## Creating Custom Prompts Define custom prompts in your `config.toml` file - no code changes or recompilation needed! ### Example ```toml [[prompts]] name = "check-pod-logs" title = "Check Pod Logs" description = "Quick way to check pod logs" [[prompts.arguments]] name = "pod_name" description = "Name of the pod" required = true [[prompts.arguments]] name = "namespace" description = "Namespace of the pod" required = false [[prompts.messages]] role = "user" content = "Show me the logs for pod {{pod_name}} in {{namespace}}" [[prompts.messages]] role = "assistant" content = "I'll retrieve and analyze the logs for you." ``` ## Configuration Reference ### Prompt Fields - **name** (required): Unique identifier for the prompt - **title** (optional): Human-readable display name - **description** (required): Brief explanation of what the prompt does - **arguments** (optional): List of parameters the prompt accepts - **messages** (required): Conversation template with role/content pairs ### Argument Fields - **name** (required): Argument identifier - **description** (optional): Explanation of the argument's purpose - **required** (optional): Whether the argument must be provided (default: false) ### Argument Substitution Use `{{argument_name}}` placeholders in message content. The template engine replaces these with actual values when the prompt is called. ## Configuration File Location Place your prompts in the `config.toml` file used by the MCP server. Specify the config file path using the `--config` flag when starting the server. ## Toolset Prompts Toolsets can provide built-in prompts by implementing the `GetPrompts()` method. This allows toolset developers to ship workflow templates alongside their tools. ### Implementing Toolset Prompts ```go func (t *MyToolset) GetPrompts() []api.ServerPrompt { return []api.ServerPrompt{ { Prompt: api.Prompt{ Name: "my-workflow", Description: "Custom workflow for my toolset", Arguments: []api.PromptArgument{ { Name: "namespace", Description: "Target namespace", Required: true, }, }, }, Handler: func(params api.PromptHandlerParams) (*api.PromptCallResult, error) { args := params.GetArguments() namespace := args["namespace"] // Build messages dynamically based on arguments messages := []api.PromptMessage{ { Role: "user", Content: api.PromptContent{ Type: "text", Text: fmt.Sprintf("Help me with namespace: %s", namespace), }, }, } return api.NewPromptCallResult("Workflow description", messages, nil), nil }, }, } } ``` ### Prompt Merging When both toolset and config prompts exist: - Config-defined prompts **override** toolset prompts with the same name - This allows administrators to customize built-in workflows - Prompts with unique names from both sources are available