Official MCP TypeScript SDK for Server & Client Development

MCP TypeScript SDK: Simplifying LLM Context Management with Model Context Protocol

In the rapidly evolving landscape of Large Language Model (LLM) development, managing context efficiently has become a critical challenge for developers. The MCP TypeScript SDK (Model Context Protocol) emerges as a game-changing solution, providing a standardized framework for building context-aware LLM applications. With over 9,900 stars on GitHub since its release in September 2024, this official TypeScript protocol implementation has quickly gained traction among developers seeking to streamline how LLMs interact with external data and tools.

The Model Context Protocol separates the concerns of context provision from LLM interaction, enabling developers to create more modular, maintainable, and scalable AI applications. This comprehensive MCP server client SDK offers a robust set of features that simplify both server and client implementation, making it an essential tool for any developer working with LLMs in TypeScript environments.

Understanding the Model Context Protocol (MCP)

At its core, the Model Context Protocol (MCP) is designed to standardize how applications provide context to LLMs. Before MCP, developers faced significant challenges in managing how LLMs access external data, tools, and resources. Each LLM integration often required custom solutions for context management, leading to code duplication, compatibility issues, and maintenance headaches.

MCP addresses these challenges by establishing a common language for LLM context management. The protocol defines standard ways to:

• Expose data through resources (similar to RESTful endpoints)
• Provide functionality through tools (reusable functions LLMs can call)
• Define interaction patterns through prompts (reusable templates)
• Handle authentication and session management
• Enable streaming responses through Streamable HTTP transport

As the official implementation of this protocol, the MCP TypeScript SDK provides developers with a production-ready toolkit that eliminates the need for building custom context management systems from scratch.

Core Features of the MCP TypeScript SDK

The MCP TypeScript SDK stands out with its comprehensive feature set that caters to both MCP server SDK and MCP client SDK development. Let's explore its most powerful capabilities:

Unified Server and Client Implementation

One of the SDK's most significant advantages is its unified approach to both server and client development. This means developers can use the same library to:

// Server implementation example
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";

const server = new McpServer({
  name: "my-llm-server",
  version: "1.0.0"
});

// Register resources, tools, and prompts
server.registerResource("user-data", ...);
server.registerTool("calculator", ...);

// Connect using stdio transport
const transport = new StdioServerTransport();
await server.connect(transport);

// Client implementation example
import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";

const client = new Client({
  name: "my-llm-client",
  version: "1.0.0"
});

// Connect to the server
const transport = new StdioClientTransport({
  command: "node",
  args: ["server.js"]
});
await client.connect(transport);

// Interact with the server
const userData = await client.readResource({ uri: "user-data://current" });

This unified approach ensures consistency across the entire development stack and reduces the learning curve associated with working with the protocol.

Flexible Transport Options

The SDK provides multiple transport mechanisms to suit different deployment scenarios:

• Stdio transport: Ideal for local development, CLI tools, and scenarios where MCP servers run as subprocesses
• Streamable HTTP transport: Perfect for remote server deployments, enabling efficient communication over HTTP with support for streaming responses
• Legacy SSE support: For backward compatibility with older implementations

This flexibility makes the Streamable HTTP SDK suitable for everything from local development environments to production-grade distributed systems.

Rich Context Management Capabilities

At its core, the SDK excels at managing LLM context through three primary abstractions:

Resources - Structured data providers that expose information to LLMs:

// Dynamic resource with parameters
server.registerResource(
  "user-profile",
  new ResourceTemplate("users://{userId}/profile", { list: undefined }),
  {
    title: "User Profile",
    description: "User profile information"
  },
  async (uri, { userId }) => ({
    contents: [{
      uri: uri.href,
      text: `Profile data for user ${userId}`
    }]
  })
);

Tools - Reusable functions that LLMs can execute to perform actions:

// Weather fetching tool example
server.registerTool(
  "fetch-weather",
  {
    title: "Weather Fetcher",
    description: "Get weather data for a city",
    inputSchema: { city: z.string() }
  },
  async ({ city }) => {
    const response = await fetch(`https://api.weather.com/${city}`);
    const data = await response.text();
    return { content: [{ type: "text", text: data }] };
  }
);

Prompts - Reusable templates that guide LLM interactions:

server.registerPrompt(
  "code-review",
  {
    title: "Code Review",
    description: "Review code for best practices",
    argsSchema: { code: z.string() }
  },
  ({ code }) => ({
    messages: [{
      role: "user",
      content: { type: "text", text: `Please review this code:\n\n${code}` }
    }]
  })
);

These abstractions form the foundation of effective LLM context SDK implementation, allowing developers to separate context management from LLM interaction logic.

Advanced Features for Production Readiness

The SDK includes several advanced features that make it suitable for production environments:

• Dynamic server configuration: Modify server capabilities on the fly without restarting
• Session management: Maintain stateful interactions with clients
• Notification debouncing: Improve network efficiency by consolidating rapid updates
• DNS rebinding protection: Enhance security for local server deployments
• Backwards compatibility: Support for older protocol versions and transport methods
• Elicitation framework: Enable interactive workflows requiring user input

Getting Started with MCP TypeScript SDK

Getting started with the MCP TypeScript SDK is straightforward. The installation process follows standard npm package conventions:

npm install @modelcontextprotocol/sdk

⚠️ Note: MCP requires Node.js v18.x or higher to function properly.

Once installed, you can quickly create a basic MCP server with a few lines of code:

import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";

// Create server instance
const server = new McpServer({
  name: "demo-server",
  version: "1.0.0"
});

// Register a simple addition tool
server.registerTool("add",
  {
    title: "Addition Tool",
    description: "Add two numbers",
    inputSchema: { a: z.number(), b: z.number() }
  },
  async ({ a, b }) => ({
    content: [{ type: "text", text: String(a + b) }]
  })
);

// Start the server with stdio transport
const transport = new StdioServerTransport();
await server.connect(transport);
console.log("MCP server running...");

This simplicity of getting started, combined with the depth of advanced features, makes the SDK accessible to developers of all skill levels while remaining powerful enough for enterprise-grade applications.

Advanced Application Scenarios

Beyond basic implementation, the MCP TypeScript SDK supports a variety of advanced application scenarios that address common challenges in LLM development:

Building Interactive LLM Applications

The SDK's elicitation framework enables the creation of interactive applications that can request additional information from users when needed:

// Restaurant booking tool with user elicitation
server.tool(
  "book-restaurant",
  { restaurant: z.string(), date: z.string(), partySize: z.number() },
  async ({ restaurant, date, partySize }) => {
    const available = await checkAvailability(restaurant, date, partySize);
    
    if (!available) {
      // Ask user for alternative preferences
      const result = await server.server.elicitInput({
        message: `No tables available at ${restaurant} on ${date}. Would you like to check alternative dates?`,
        requestedSchema: {
          checkAlternatives: z.boolean(),
          flexibleDates: z.enum(["next_day", "same_week", "next_week"])
        }
      });
      
      // Process user response
      if (result.action === "accept" && result.content?.checkAlternatives) {
        // Find and suggest alternatives
        const alternatives = await findAlternatives(
          restaurant, date, partySize, result.content.flexibleDates
        );
        return { content: [{ type: "text", text: `Alternatives: ${alternatives.join(", ")}` }] };
      }
    }
    // Proceed with booking if available
    return { content: [{ type: "text", text: "Booking confirmed!" }] };
  }
);

Implementing Efficient Resource Loading

The SDK's ResourceLink feature allows tools to return references to resources rather than embedding their full content, significantly improving performance with large files or numerous resources:

// Tool returning resource links instead of full content
server.registerTool(
  "list-project-files",
  {
    title: "List Project Files",
    description: "List files in the project directory",
    inputSchema: { pattern: z.string() }
  },
  async ({ pattern }) => ({
    content: [
      { type: "text", text: `Files matching "${pattern}":` },
      // Return links instead of full file content
      {
        type: "resource_link",
        uri: "file:///project/src/main.ts",
        name: "main.ts",
        mimeType: "text/typescript"
      },
      {
        type: "resource_link",
        uri: "file:///project/package.json",
        name: "package.json",
        mimeType: "application/json"
      }
    ]
  })
);

Clients can then selectively load only the resources they need, reducing bandwidth usage and improving response times.

Creating Stateful Server Sessions

For applications requiring stateful interactions, the SDK supports session management with Streamable HTTP transport:

// Express server with session management
import express from "express";
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StreamableHTTPServerTransport } from "@modelcontextprotocol/sdk/server/streamableHttp.js";
import { randomUUID } from "node:crypto";

const app = express();
app.use(express.json());

// Store active transports by session ID
const transports = {};

app.post('/mcp', async (req, res) => {
  const sessionId = req.headers['mcp-session-id'] as string;
  let transport;
  
  if (sessionId && transports[sessionId]) {
    // Reuse existing session
    transport = transports[sessionId];
  } else {
    // Create new session
    transport = new StreamableHTTPServerTransport({
      sessionIdGenerator: () => randomUUID()
    });
    
    // Store transport and set up cleanup
    transports[transport.sessionId] = transport;
    transport.onclose = () => {
      delete transports[transport.sessionId];
    };
    
    // Create and configure server instance
    const server = new McpServer({ name: "stateful-server", version: "1.0.0" });
    // Register server components...
    await server.connect(transport);
  }
  
  // Handle the request
  await transport.handleRequest(req, res, req.body);
});

app.listen(3000, () => console.log("MCP server listening on port 3000"));

This session management capability is essential for building interactive applications that maintain context across multiple interactions.

Real-World Applications and Use Cases

The MCP TypeScript SDK has proven valuable across various industries and application types. Here are some notable use cases:

Developer Tools Integration

IDEs and developer tools are leveraging the SDK to provide LLM-powered assistance with code understanding and generation. By exposing project structure, dependencies, and codebase context through MCP resources, these tools can offer more accurate and relevant suggestions.

Data Analysis Platforms

Data analysis platforms use MCP tools to enable LLMs to execute queries against databases, generate visualizations, and interpret results. The SDK's structured approach to tool definition ensures secure and controlled execution of data operations.

Customer Support Systems

Customer support platforms are implementing MCP servers to provide LLMs with context about customer history, product information, and support procedures. This allows for more personalized and accurate support interactions without exposing sensitive systems directly to LLMs.

Educational Applications

Educational technology platforms use MCP prompts and resources to create adaptive learning experiences. The SDK's elicitation capabilities enable interactive tutoring systems that can assess student understanding and provide targeted guidance.

Comparing MCP TypeScript SDK with Alternatives

While there are several approaches to LLM context management, the MCP TypeScript SDK offers unique advantages:

This comparison highlights why the TypeScript protocol implementation provided by the MCP SDK offers a more robust, secure, and maintainable approach to LLM context management than ad-hoc solutions or traditional API integration patterns.

Conclusion: The Future of LLM Context Management

As LLM applications continue to grow in complexity, the need for standardized context management becomes increasingly critical. The MCP TypeScript SDK addresses this need by providing a comprehensive, flexible framework for building context-aware LLM applications.

By separating context provision from LLM interaction, the SDK enables developers to create more modular, maintainable, and secure applications. Its rich feature set—including resources, tools, prompts, and advanced transport options—supports everything from simple scripts to enterprise-grade applications.

Whether you're building developer tools, customer support systems, educational platforms, or data analysis applications, the MCP client SDK and MCP server SDK components provide the building blocks needed for effective LLM integration.

As the Model Context Protocol evolves and gains wider adoption, the MCP TypeScript SDK will undoubtedly play a crucial role in shaping the future of LLM application development, making it easier for developers to harness the full potential of these powerful AI models while maintaining control, security, and efficiency.

For developers working with LLMs in TypeScript environments, adopting the MCP TypeScript SDK represents a significant step forward in building more robust, maintainable, and effective AI-powered applications.