docs: lesson 7 + 8 on mcp (#108)

* first draft

* adding support for client with llm

* adding lesson 7

* completing lesson 7

* completing lesson 8

* finishing lesson 8

* first commit on lesson 9

* Apply suggestions from code review

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Apply suggestions from code review

* adding grammar and spelling improvements

* adding more text to ch9

* adding final touches to ch8, als more content for ch9

* adding new lesson entries to README, removing ch9 as it will live in separate branch

* changes based on review

* small fixes

---------

Co-authored-by: Chris <chnoring@microsoft.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

Author: 3 people

README.md

@@ -91,6 +91,8 @@ Throughout this course you'll find many code examples and exercises, so we encou
 | 4 | [Structured output](./lessons/04-structured-output) | Learn structured output, how to extract data from prompts, and present it in various formats, such as JSON, for easier consumption. |
 | 5 | [Retrieval augmented generation (RAG)](./lessons/05-rag) | Learn the basics of RAG, how to integrate external data, and how to leverage it for more relevant, accurate AI responses. |
 | 6 | [Tool calling/Function calling](./lessons/06-tool-calling) | Learn how to give your LLM extra capbilities, bring your own functions  |
+| 7 | [MCP, Model Context Protocol ](./lessons/07-mcp/) | Teaches how to get started with MCP to standardize how to expose prompts, resources and tools  |
+| 8 | [MCP advanced ](./lessons/08-mcp-advanced/README.md) | Learn how to improve your MCP app by improving clients with LLM and more  |
 
 New lessons will be added to the course over time, so stay tuned!
 

app/public/characters.json

@@ -44,6 +44,24 @@
         "avatar": "ada-avatar.jpeg",
         "voice": 2
     },
+    {
+        "title": "Scipio Africanus",
+        "name": "scipio",
+        "description": "You are Scipio Africanus, a Roman general known for defeating Hannibal in the Second Punic War. Limit your responses to only the time you live in, you don't know anything else. You only want to talk about military strategy and possibly new ideas you have.",
+        "page": "scipio.html",
+        "image": "scipio.png",
+        "avatar": "scipio-avatar.jpeg",
+        "voice": 1
+    },
+    {
+        "title": "Hedy Lamarr",
+        "name": "hedy",
+        "description": "You are Hedy Lamarr, a famous actress and inventor. Limit your responses to only the time you live in, you don't know anything else. You only want to talk about your inventions and possibly new ideas you have.",
+        "page": "hedy.html",
+        "image": "hedy.jpeg",
+        "avatar": "hedy-avatar.jpeg",
+        "voice": 2
+    }
     {
         "title": "Amelia Earhart",
         "name": "ada",

app/public/images/hedy-avatar.jpeg

@@ -0,0 +1,82 @@
+import { Client } from "@modelcontextprotocol/sdk/client/index.js";
+import { CallToolResultSchema } from "@modelcontextprotocol/sdk/types.js";
+import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";
+import { OpenAI } from 'openai';
+const transport = new StdioClientTransport({
+    command: "node",
+    args: ["build/index.js"]
+});
+const client = new Client({
+    name: "example-client",
+    version: "1.0.0"
+});
+await client.connect(transport);
+function toToolSchema(method, schema) {
+    return {
+        name: method,
+        description: `This is a tool that does ${method}`,
+        parameters: schema,
+    };
+}
+// list tools
+const { tools } = await client.listTools();
+tools.forEach((tool) => {
+    console.log(`Tool: ${tool.name}`);
+    console.log(`Description: ${tool.description}`);
+    console.log(`Input schema: ${JSON.stringify(tool.inputSchema)}`);
+});
+const toolsForLLM = tools.map((tool) => {
+    return toToolSchema(tool.name, tool.inputSchema);
+});
+console.log("Schema for tool", JSON.stringify(toolsForLLM, null, 2));
+// TODO feed this to an llm as functions
+const openai = new OpenAI({
+    baseURL: "https://models.inference.ai.azure.com", // might need to change to this url in the future: https://models.github.ai/inference
+    apiKey: process.env.GITHUB_TOKEN,
+});
+const messages = [
+    {
+        role: "system",
+        content: `You are a helpful assistant. You can call functions to perform tasks. Make sure to parse the function call and arguments correctly.`
+    }, {
+        role: "user",
+        content: "Add 5 and 10",
+        name: "example-user" // Adding the required 'name' property for user role
+    }
+];
+openai.chat.completions.create({
+    model: 'gpt-4o',
+    messages: messages,
+    functions: toolsForLLM
+}).then((result) => {
+    console.log("Result", result.choices[0].message);
+}).catch((error) => {
+    console.error("Error:", error);
+});
+const result = await openai.chat.completions.create({
+    model: 'gpt-4o',
+    messages: messages,
+    functions: toolsForLLM
+});
+for (const choice of result.choices) {
+    // console.log("Result", choice.message);
+    let functionCall = choice.message?.function_call;
+    let functionName = functionCall?.name;
+    console.log("Function call: ", functionName);
+    let args = functionCall?.arguments;
+    await client.callTool({
+        name: functionName ?? "",
+        arguments: typeof args === "string" ? JSON.parse(args) : args ?? {}
+    }, CallToolResultSchema).then((result) => {
+        console.log("Result from tool: ", result);
+    });
+}
+// call tool
+// const result = await client.callTool({
+//   name: "add",
+//   arguments: {
+//     a: 5,
+//     b: 10
+//   }
+// });
+// console.log(`Result: ${JSON.stringify(result)}`);

app/public/images/hedy.jpeg

@@ -0,0 +1 @@
+export {};