feat: add getPromptContent tool for auto-discovery

- Add MCP tool that dynamically discovers all available prompts
- Tool description includes comprehensive list of all prompts with descriptions
- Auto-generates enum of available prompts from markdown frontmatter
- Enables LLM auto-discovery of TimescaleDB guidance prompts
- Updated timescaledb setup prompt description to be more comprehensive

Benefits:
- LLM can automatically choose appropriate prompts based on user needs
- No need for users to explicitly know prompt names
- Stays in sync as new .md files are added

Author: cevian

src/apis/getPromptContent.ts

@@ -0,0 +1,90 @@
+import { z } from 'zod';
+import { readdirSync, readFileSync } from 'fs';
+import { join, dirname } from 'path';
+import { fileURLToPath } from 'url';
+import matter from 'gray-matter';
+import { ApiFactory } from '../shared/boilerplate/src/types.js';
+import { ServerContext } from '../types.js';
+import { promptFactories } from '../prompts/index.js';
+
+// Get all available prompt names dynamically from markdown files
+const __dirname = dirname(fileURLToPath(import.meta.url));
+const markdownPromptsDir = join(__dirname, '../prompts/md');
+
+function getAvailablePrompts() {
+  const files = readdirSync(markdownPromptsDir).filter(file => file.endsWith('.md'));
+  const prompts = files.map(file => {
+    const filePath = join(markdownPromptsDir, file);
+    const fileContent = readFileSync(filePath, 'utf-8');
+    const { data } = matter(fileContent);
+    return {
+      name: data.name,
+      title: data.title,
+      description: data.description,
+    };
+  });
+  return prompts;
+}
+
+const availablePrompts = getAvailablePrompts();
+const promptNames = availablePrompts.map(p => p.name);
+
+// Create enum schema dynamically
+const inputSchema = {
+  prompt_name: z
+    .enum(promptNames as [string, ...string[]])
+    .describe('The name of the prompt to retrieve'),
+} as const;
+
+const outputSchema = {
+  prompt_name: z.string().describe('The name of the requested prompt'),
+  title: z.string().describe('The display title of the prompt'),
+  description: z.string().describe('Description of what this prompt does'),
+  content: z.string().describe('The full prompt content'),
+} as const;
+
+export const getPromptContentFactory: ApiFactory<
+  ServerContext,
+  typeof inputSchema,
+  typeof outputSchema
+> = ({ pgPool }) => ({
+  name: 'getPromptContent',
+  config: {
+    title: 'Get TimescaleDB Prompt Content',
+    description: `Retrieve detailed prompt content for TimescaleDB guidance and best practices. This tool provides access to comprehensive guides that help with TimescaleDB implementation.
+
+Available Prompts:
+
+${availablePrompts.map(p => `**${p.name}** - ${p.description}`).join('\n\n')}
+`,
+    inputSchema,
+    outputSchema,
+  },
+  fn: async ({ prompt_name }) => {
+    // Find the prompt factory by name
+    const promptFactory = promptFactories.find(factory => {
+      const prompt = factory({} as ServerContext);
+      return prompt.name === prompt_name;
+    });
+
+    if (!promptFactory) {
+      throw new Error(`Prompt '${prompt_name}' not found`);
+    }
+
+    // Create the prompt instance
+    const prompt = promptFactory({} as ServerContext);
+
+    // Execute the prompt to get its content
+    const result = await prompt.fn({});
+
+    // Extract content from the prompt result
+    const content = result.messages?.[0]?.content?.text || '';
+
+    return {
+      prompt_name: prompt.name,
+      title: prompt.config.title || prompt.name,
+      description: prompt.config.description || '',
+      content: String(content),
+    };
+  },
+});

src/apis/index.ts

@@ -1,7 +1,9 @@
 import { semanticSearchPostgresDocsFactory } from './semanticSearchPostgresDocs.js';
 import { semanticSearchTimescaleDocsFactory } from './semanticSearchTimescaleDocs.js';
+import { getPromptContentFactory } from './getPromptContent.js';
 
 export const apiFactories = [
   semanticSearchPostgresDocsFactory,
   semanticSearchTimescaleDocsFactory,
+  getPromptContentFactory,
 ] as const;

src/prompts/md/timescaledb_setup_prompt.md

@@ -1,7 +1,7 @@
 ---
 name: timescaledbSetup
 title: TimescaleDB Complete Setup Guide
-description: Step-by-step instructions for setting up TimescaleDB with hypertables, compression, retention policies, and continuous aggregates
+description: Step-by-step instructions for designing table schemas and setting up TimescaleDB with hypertables, indexes, compression, retention policies, and continuous aggregates. Instructions for selecting: partition columns, segment_by columns, order_by columns, chunk time interval, real-time aggregation.
 ---
 
 # TimescaleDB Complete Setup Guide for AI Coding Assistants