chore: import upstream snapshot with attribution

04-PracticalImplementation/samples/javascript/README.md

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+# Sample
+
+This is a JavaScript sample for an MCP Server
+
+Here's an example of a tool registration where we register a tool that makes a mock call to an LLM:
+
+```javascript
+this.mcpServer.tool(
+    'completion',
+    {
+    model: z.string(),
+    prompt: z.string(),
+    options: z.object({
+        temperature: z.number().optional(),
+        max_tokens: z.number().optional(),
+        stream: z.boolean().optional()
+    }).optional()
+    },
+    async ({ model, prompt, options }) => {
+    console.log(`Processing completion request for model: ${model}`);
+    
+    // Validate model
+    if (!this.models.includes(model)) {
+        throw new Error(`Model ${model} not supported`);
+    }
+    
+    // Emit event for monitoring/metrics
+    this.events.emit('request', { 
+        type: 'completion', 
+        model, 
+        timestamp: new Date() 
+    });
+    
+    // In a real implementation, this would call an AI model
+    // Here we just echo back parts of the request with a mock response
+    const response = {
+        id: `mcp-resp-${Date.now()}`,
+        model,
+        text: `This is a response to: ${prompt.substring(0, 30)}...`,
+        usage: {
+        promptTokens: prompt.split(' ').length,
+        completionTokens: 20,
+        totalTokens: prompt.split(' ').length + 20
+        }
+    };
+    
+    // Simulate network delay
+    await new Promise(resolve => setTimeout(resolve, 500));
+    
+    // Emit completion event
+    this.events.emit('completion', {
+        model,
+        timestamp: new Date()
+    });
+    
+    return {
+        content: [
+        {
+            type: 'text',
+            text: JSON.stringify(response)
+        }
+        ]
+    };
+    }
+);
+```
+
+## Install
+
+Run the following command:
+
+```bash
+npm install
+```
+
+## Run
+
+```bash
+npm start
+```