Prompts

Prompts generate message sequences that can be used to start or continue LLM conversations.

Basic Prompt

Return a fixed message sequence.

server.prompt("greet", {
  description: "Generate a greeting",
  handler: () => ({
    messages: [{
      role: "user",
      content: { type: "text", text: "Hello, how are you?" }
    }]
  })
});

Prompt with Arguments

Validate prompt arguments before building messages.

import { z } from "zod";

const SummarySchema = z.object({
  text: z.string(),
  length: z.enum(["short", "medium", "long"]).optional(),
});

server.prompt("summarize", {
  description: "Create a summary prompt",
  arguments: SummarySchema,
  handler: (args) => ({
    description: "Summarization prompt",
    messages: [{
      role: "user",
      content: {
        type: "text",
        text: `Please summarize this text in ${args.length || "medium"} length:\n\n${args.text}`
      }
    }]
  })
});

Prompt with Metadata

Add title and _meta to pass additional information through prompts/list and prompts/get responses.

server.prompt("research-assistant", {
  description: "Research assistant prompt with context",
  title: "Research Assistant",
  _meta: {
    category: "research",
    complexity: "advanced",
    estimatedTokens: 500,
  },
  arguments: [
    { name: "topic", description: "Research topic", required: true },
    { name: "depth", description: "Research depth", required: false },
  ],
  handler: (args: { topic: string; depth?: string }) => ({
    messages: [{
      role: "user",
      content: {
        type: "text",
        text: `Research ${args.topic} at ${args.depth || "medium"} depth`
      }
    }],
    _meta: {
      templateVersion: "2.0",
      generated: true,
    },
  })
});

The _meta and title from the definition appear in prompts/list responses. Handlers can also return _meta in the result for per-generation metadata.

Next Steps

• Type Safety - Understand schema validation
• Tools - Define callable functions