Integrate Brave Search capabilities into Claude through MCP. Enables real-time web searches with privacy-focused results and comprehensive web coverage.
What is Brave Search MCP
MCP TypeScript SDK !NPM Version !MIT licensed
Table of Contents
- Overview
- Installation
- Quickstart
- What is MCP?
- Core Concepts
- Running Your Server
- Examples
- Advanced Usage
Overview
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
Installation
npm install @modelcontextprotocol/sdk
Quick Start
Let's create a simple MCP server that exposes a calculator tool and some data:
import { McpServer, ResourceTemplate } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.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",
new ResourceTemplate("greeting://{name}", { list: undefined }),
async (uri, { name }) => ({
contents: [{
uri: uri.href,
text: `Hello, ${name}!`
}]
})
);
// Start receiving messages on stdin and sending messages on stdout
const transport = new StdioServerTransport();
await server.connect(transport);
What is MCP?
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!
Core Concepts
Server
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
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",
new ResourceTemplate("users://{userId}/profile", { list: undefined }),
async (uri, { userId }) => ({
contents: [{
uri: uri.href,
text: `Profile data for user ${userId}`
}]
})
);
Tools
Tools let LLMs take actions through your server. Unlike resources, tools are expected to perform computation and have side effects:
// Simple tool with parameters
server.tool(
"calculate-bmi",
{
weightKg: z.number(),
heightM: z.number()
},
async ({ weightKg, heightM }) => ({
content: [{
type: "text",
text: String(weightKg / (heightM * heightM))
}]
})
);
// Async tool with external API call
server.tool(
"fetch-weather",
{ city: z.string() },
async ({ city }) => {
const response = await fetch(`https://api.weather.com/${city}`);
const data = await response.text();
return {
content: [{ type: "text", text: data }]
};
}
);
Prompts
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}`
}
}]
})
);
Running Your Server
MCP servers in TypeScript need to be connected to a transport to communicate with clients. How you start the server depends on the choice of transport:
stdio
For command-line tools and direct integrations:
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
const server = new McpServer({
name: "example-server",
version: "1.0.0"
});
// ... set up server resources, tools, and prompts ...
const transport = new StdioServerTransport();
await server.connect(transport);
HTTP with SSE
For remote servers, start a web server with a Server-Sent Events (SSE) endpoint, and a separate endpoint for the client to send its messages to:
import express, { Request, Response } from "express";
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { SSEServerTransport } from "@modelcontextprotocol/sdk/server/sse.js";
const server = new McpServer({
name: "example-server",
version: "1.0.0"
});
// ... set up server resources, tools, and prompts ...
const app = express();
// to support multiple simultaneous connections we have a lookup object from
// sessionId to transport
const transports: {[sessionId: string]: SSEServerTransport} = {};
app.get("/sse", async (_: Request, res: Response) => {
const transport = new SSEServerTransport('/messages', res);
transports[transport.sessionId] = transport;
res.on("close", () => {
delete transports[transport.sessionId];
});
await server.connect(transport);
});
app.post("/messages", async (req: Request, res: Response) => {
const sessionId = req.query.sessionId as string;
const transport = transports[sessionId];
if (transport) {
await transport.handlePostMessage(req, res);
} else {
res.status(400).send('No transport found for sessionId');
}
});
app.listen(3001);
Testing and Debugging
To test your server, you can use the MCP Inspector. See its README for more information.
Examples
Echo Server
A simple server demonstrating resources, tools, and prompts:
import { McpServer, ResourceTemplate } from "@modelcontextprotocol/sdk/server/mcp.js";
import { z } from "zod";
const server = new McpServer({
name: "Echo",
version: "1.0.0"
});
server.resource(
"echo",
new ResourceTemplate("echo://{message}", { list: undefined }),
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}`
}
}]
})
);
SQLite Explorer
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();
}
}
);
Advanced Usage
Low-Level Server
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);
Writing MCP Clients
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({
name: "example-tool",
arguments: {
arg1: "value"
}
});
Documentation
- Model Context Protocol documentation
- MCP Specification
- Example Servers
Contributing
Issues and pull requests are welcome on GitHub at https://github.com/modelcontextprotocol/typescript-sdk.
License
This project is licensed under the MIT License—see the LICENSE file for details.
How to Use
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Frequently Asked Questions
What is MCP?
MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.
What are MCP Servers?
MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.
How do MCP Servers work?
MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.
Are MCP Servers secure?
Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.
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