ended3월 14일· 15 sources
Building MCP Servers: Extend AI with Custom Tools
MCP 서버 구축: 커스텀 도구로 AI 확장하기
Why it matters
The article explains the Model Context Protocol (MCP), a standardized way for LLMs like Claude and GPT to dynamically interact with external tools and data sources at runtime. It covers the MCP request-response lifecycle and guides readers through building a custom MCP server in TypeScript to connect LLMs to internal systems such as CRMs, databases, and documentation.
15
Sources
+0
24h
—
Growth
190d
Active
gptCrawlForgeReal-time dataanthropicdeveloper integrationGitHubModel Context Protocol
Sources
devto
Building MCP Servers: Extend AI with Custom Tools3월 14일
devtoDocShark: a local-first documentation MCP server for AI3월 19일
devtoWhat MCP Actually Is (And Why It Exists)3월 21일
devtoCode Generation MCP Servers — UI Components, Context Providers, and the Paradox of AI Writing Its Own Tools3월 25일
devtoThe Complete Guide to MCP Web Scraping: Everything Developers Need to Know3월 28일
devtogithub/github-mcp-server3월 28일
devtoMCP vs Everything Else: A Practical Decision Guide3월 26일
devtoBuild a Production-Ready Review Analytics MCP Server with TypeScript, Rules, LLMs, and Vector Search3월 15일
devtoThe #1 Most Popular MCP Server Gets an F3월 24일
devtoAI-Safe MCP Server for SQL3월 23일
devtoAnnouncing the Colab MCP Server: Connect Any AI Agent to Google Colab3월 17일
devtoThe MCP Pattern: SQLite as the AI-Queryable Cache3월 21일
devtoThe PostgreSQL MCP Server — Read-Only Protection That Wasn't3월 26일
devtoContext7 MCP Server — Real-Time Library Docs for AI Coding Agents3월 24일
devtoBoost Your Agents with MCPs - Productivity Customized Tools3월 22일