Building an MCP Server: Step-by-Step Tutorial

Building an MCP server lets you create custom tool integrations that work with any MCP-compatible AI client. This tutorial walks you through creating a server from scratch in both TypeScript and Python.

Overview

An MCP server exposes tools, resources, and prompts to AI clients through a standardized protocol. Building one involves defining your tools with schemas, implementing their logic, and setting up the transport layer. The official SDKs handle the protocol details, so you can focus on your tool logic.

Key Features

• Tool Definition — Define tools with JSON Schema input/output specifications
• Resource Exposure — Serve data as structured resources for AI consumption
• Prompt Templates — Provide reusable prompt templates for common operations
• Transport Options — stdio for local, HTTP/SSE for remote deployment
• Error Handling — Structured error responses for graceful failure handling

Getting Started

TypeScript example:

import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";

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

server.tool("get_data", { query: { type: "string" } }, async ({ query }) => {
  const result = await fetchData(query);
  return { content: [{ type: "text", text: JSON.stringify(result) }] };
});

Use Cases

• Internal APIs — Expose company APIs to AI agents securely
• Database Access — Controlled database querying through MCP
• Custom Tools — Domain-specific tools for specialized workflows
• Legacy Integration — Bridge legacy systems with modern AI tools

Best Practices

• Write clear tool descriptions — AI agents rely on descriptions to choose the right tool
• Validate inputs — Always validate tool inputs before processing
• Handle errors gracefully — Return structured errors instead of throwing exceptions
• Test thoroughly — Test with multiple MCP clients to ensure compatibility

Frequently Asked Questions

Conclusion

Stay ahead of the curve by exploring our comprehensive directories. Browse the AI Agent directory with 400+ agents and the MCP Server directory with 2,300+ servers to find the perfect tools for your workflow.