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Get Started with MCP

Follow these steps to start using Model Context Protocol in your AI applications.

1

Install the MCP package

Install the MCP package using your favorite package manager. MCP works with Node.js, Python, and other environments.

npm
npm install @modl/mcp
yarn
yarn add @modl/mcp
2

Create your first MCP context

Define your context schema and create your first MCP context instance. This example shows a simple assistant with basic memory and tools.

index.js
import { MCPContext } from '@modl/mcp';

// Create a simple assistant context
const assistant = new MCPContext({
  systemInstruction: "You are a helpful assistant.",
  userGoal: "Answer questions about programming",
  memory: {
    shortTerm: [],
    longTerm: {
      userPreferences: {
        codeExamples: true,
        detailedExplanations: true
      }
    }
  },
  tools: [
    {
      name: "searchDocumentation",
      description: "Search programming documentation",
      parameters: {
        query: "string",
        language: "string"
      }
    }
  ]
});

// Export the context
export default assistant;
3

Use with your LLM provider

MCP works with any LLM provider. Here's an example using OpenAI, but you can use Anthropic, Gemini, or any other provider.

openai-example.js
import OpenAI from 'openai';
import assistant from './index.js';

const openai = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY,
});

async function main() {
  // Compile the context for OpenAI
  const context = assistant.compileFor('openai');
  
  // Use the context in your OpenAI call
  const response = await openai.chat.completions.create({
    model: 'gpt-4o',
    messages: [
      {
        role: 'system',
        content: context.systemMessage
      },
      {
        role: 'user',
        content: 'How do I use async/await in JavaScript?'
      }
    ],
    tools: context.tools
  });
  
  console.log(response.choices[0].message.content);
}

main();

Next Steps

Now that you've created your first MCP context, explore these resources to learn more: