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개발자용 MCP 서버와 함께 자주 쓰이는 AI 코드 에디터.

11766개 결과

MCP Servers

5533 개 결과

A conversational AI agent and voice assistant application built with the LiveKit Agents framework, capable of using Model Context Protocol (MCP) tools to interact with external services for SRE and...

71 060

covagashi/eplan-rag-mcp

Developer tools

A collection of AI-assisted automation tools for and , built around the Model Context Protocol (MCP).

72 060

azure-samples/mcp-auth-servers

Developer tools

Reference servers that demo how authentication works with the current Model Context Protocol spec.

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christian-posta/mcp-auth-step-by-step

Developer tools

This repository demonstrates building an MCP (Model Context Protocol) server with HTTP transport and JWT authentication, progressing through iterative steps.

62 060

codeglide/codeglide-mcpgen

API development

Generation of Secure MCP (Model Context Protocol) Servers from API source code at Scale

76 060

eyalbenba/claude-code-mcp-init

Developer tools

A lightweight CLI tool to easily configure and initialize MCPs for Claude Code.

70 060

sdd330/feishu-mcp-server

Developer tools

飞书MCP服务器是一个基于Model Context Protocol的服务，提供飞书API集成，使AI模型能够轻松与飞书服务交互。

54 060

trendmicro/vision-one-mcp-server

Deployment & DevOps

The Trend Vision One Model Context Protocol (MCP) Server enables natural language interaction between your favourite AI tooling and the Trend Vision One web APIs.

38 060

wanaku-ai/wanaku

Developer tools

The Wanaku MCP Router is a router for AI-enabled applications powered by the Model Context Protocol (MCP).

129 060

damienbench/a2a-mcp-webhook-workshop

Developer tools

This project demonstrates how to build a multi-agent system using Agent-to-Agent (A2A) communication with the Model Context Protocol (MCP).

53 060

camel-ai/mcpify

Developer tools

is a powerful tool that automatically detects APIs in existing projects and transforms them into Model Context Protocol (MCP) servers.

67 060

shinzo-labs/shinzo

Analytics & monitoring

Complete observability platform for AI agents and MCP servers. Improve your AI deployment outcomes, identify inference inefficiencies, and gain insights into real agent usage patterns.

33 060