- Overview
- Installation
- Quickstart
- What is MCP?
- Core Concepts
- Running Your Server
- Examples
- Advanced Usage
The Model Context Protocol allows applications to provide context for LLMs in a standardized way, separating the concerns of providing context from the actual LLM interaction. This TypeScript SDK implements the full MCP specification, making it easy to:
- Build MCP clients that can connect to any MCP server
- Create MCP servers that expose resources, prompts and tools
- Use standard transports like stdio and SSE
- Handle all MCP protocol messages and lifecycle events
npm install @modelcontextprotocol/sdkLet's create a simple MCP server that exposes a calculator tool and some data:
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { z } from "zod";
// Create an MCP server
const server = new McpServer({
name: "Demo",
version: "1.0.0"
});
// Add an addition tool
server.tool("add",
{ a: z.number(), b: z.number() },
async ({ a, b }) => ({
content: [{ type: "text", text: String(a + b) }]
})
);
// Add a dynamic greeting resource
server.resource(
"greeting",
"greeting://{name}",
async (uri, { name }) => ({
contents: [{
uri: uri.href,
text: `Hello, ${name}!`
}]
})
);The Model Context Protocol (MCP) lets you build servers that expose data and functionality to LLM applications in a secure, standardized way. Think of it like a web API, but specifically designed for LLM interactions. MCP servers can:
- Expose data through Resources (think of these sort of like GET endpoints; they are used to load information into the LLM's context)
- Provide functionality through Tools (sort of like POST endpoints; they are used to execute code or otherwise produce a side effect)
- Define interaction patterns through Prompts (reusable templates for LLM interactions)
- And more!
The McpServer is your core interface to the MCP protocol. It handles connection management, protocol compliance, and message routing:
const server = new McpServer({
name: "My App",
version: "1.0.0"
});Resources are how you expose data to LLMs. They're similar to GET endpoints in a REST API - they provide data but shouldn't perform significant computation or have side effects:
// Static resource
server.resource(
"config",
"config://app",
async (uri) => ({
contents: [{
uri: uri.href,
text: "App configuration here"
}]
})
);
// Dynamic resource with parameters
server.resource(
"user-profile",
"users://{userId}/profile",
async (uri, { userId }) => ({
contents: [{
uri: uri.href,
text: `Profile data for user ${userId}`
}]
})
);Tools let LLMs take actions through your server. Unlike resources, tools are expected to perform computation and have side effects:
// Simple tool with parameters
server.tool(
"calculate-bmi",
{
weightKg: z.number(),
heightM: z.number()
},
async ({ weightKg, heightM }) => ({
content: [{
type: "text",
text: String(weightKg / (heightM * heightM))
}]
})
);
// Async tool with external API call
server.tool(
"fetch-weather",
{ city: z.string() },
async ({ city }) => {
const response = await fetch(`https://api.weather.com/${city}`);
const data = await response.text();
return {
content: [{ type: "text", text: data }]
};
}
);Prompts are reusable templates that help LLMs interact with your server effectively:
server.prompt(
"review-code",
{ code: z.string() },
({ code }) => ({
messages: [{
role: "user",
content: {
type: "text",
text: `Please review this code:\n\n${code}`
}
}]
})
);A simple server demonstrating resources, tools, and prompts:
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { z } from "zod";
const server = new McpServer({
name: "Echo",
version: "1.0.0"
});
server.resource(
"echo",
"echo://{message}",
async (uri, { message }) => ({
contents: [{
uri: uri.href,
text: `Resource echo: ${message}`
}]
})
);
server.tool(
"echo",
{ message: z.string() },
async ({ message }) => ({
content: [{ type: "text", text: `Tool echo: ${message}` }]
})
);
server.prompt(
"echo",
{ message: z.string() },
({ message }) => ({
messages: [{
role: "user",
content: {
type: "text",
text: `Please process this message: ${message}`
}
}]
})
);A more complex example showing database integration:
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import sqlite3 from "sqlite3";
import { promisify } from "util";
import { z } from "zod";
const server = new McpServer({
name: "SQLite Explorer",
version: "1.0.0"
});
// Helper to create DB connection
const getDb = () => {
const db = new sqlite3.Database("database.db");
return {
all: promisify<string, any[]>(db.all.bind(db)),
close: promisify(db.close.bind(db))
};
};
server.resource(
"schema",
"schema://main",
async (uri) => {
const db = getDb();
try {
const tables = await db.all(
"SELECT sql FROM sqlite_master WHERE type='table'"
);
return {
contents: [{
uri: uri.href,
text: tables.map((t: {sql: string}) => t.sql).join("\n")
}]
};
} finally {
await db.close();
}
}
);
server.tool(
"query",
{ sql: z.string() },
async ({ sql }) => {
const db = getDb();
try {
const results = await db.all(sql);
return {
content: [{
type: "text",
text: JSON.stringify(results, null, 2)
}]
};
} catch (err: unknown) {
const error = err as Error;
return {
content: [{
type: "text",
text: `Error: ${error.message}`
}],
isError: true
};
} finally {
await db.close();
}
}
);For more control, you can use the low-level Server class directly:
import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import {
ListPromptsRequestSchema,
GetPromptRequestSchema
} from "@modelcontextprotocol/sdk/types.js";
const server = new Server(
{
name: "example-server",
version: "1.0.0"
},
{
capabilities: {
prompts: {}
}
}
);
server.setRequestHandler(ListPromptsRequestSchema, async () => {
return {
prompts: [{
name: "example-prompt",
description: "An example prompt template",
arguments: [{
name: "arg1",
description: "Example argument",
required: true
}]
}]
};
});
server.setRequestHandler(GetPromptRequestSchema, async (request) => {
if (request.params.name !== "example-prompt") {
throw new Error("Unknown prompt");
}
return {
description: "Example prompt",
messages: [{
role: "user",
content: {
type: "text",
text: "Example prompt text"
}
}]
};
});
const transport = new StdioServerTransport();
await server.connect(transport);The SDK provides a high-level client interface:
import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";
const transport = new StdioClientTransport({
command: "node",
args: ["server.js"]
});
const client = new Client(
{
name: "example-client",
version: "1.0.0"
},
{
capabilities: {
prompts: {},
resources: {},
tools: {}
}
}
);
await client.connect(transport);
// List prompts
const prompts = await client.listPrompts();
// Get a prompt
const prompt = await client.getPrompt("example-prompt", {
arg1: "value"
});
// List resources
const resources = await client.listResources();
// Read a resource
const resource = await client.readResource("file:///example.txt");
// Call a tool
const result = await client.callTool("example-tool", {
arg1: "value"
});Issues and pull requests are welcome on GitHub at https://github.com/modelcontextprotocol/typescript-sdk.
This project is licensed under the MIT License—see the LICENSE file for details.
