Discover Awesome MCP Servers

Weather MCP Server

Provides real-time, historical, and forecasted weather data for any location worldwide using the Open-Meteo API. It includes specialized tools for agricultural growing conditions, weather alerts, and up to 16 days of forecasts across multiple transport modes.

Local Stock Analyst MCP

Provides comprehensive stock intelligence workflows by integrating data from multiple providers for market analysis, technical indicators, and fundamental data. It enables users to perform technical, fundamental, and risk analysis alongside options and news tracking through a unified tool registry.

Screeps World MCP Service

Integrates live Screeps game data into AI development workflows, providing comprehensive tools for room operations, market analysis, and user management. It enables AI agents to monitor game status and interact with the game world through the Model Context Protocol.

College Basketball Stats MCP Server

An MCP server for accessing college basketball statistics through the SportsData.io CBB v3 Stats API, enabling AI agents to retrieve and analyze college basketball data through natural language interactions.

PostgreSQL MCP Server

Enables direct execution of PostgreSQL queries through the Model Context Protocol. Supports both SELECT and non-SELECT operations with dual communication modes (stdio and HTTP REST API).

ExecuteAutomation Database Server

A Model Context Protocol server that enables LLMs like Claude to interact with SQLite and SQL Server databases, allowing for schema inspection and SQL query execution.

Cline Code Nexus

Cline이 MCP 서버 기능을 검증하기 위해 만든 테스트 저장소입니다.

Kaspersky OpenTIP MCP Server

Kaspersky OpenTIP Model Context Protocol Server. This server gives access to Kaspersky OpenTIP API to agentic applications.

domainkits-mcp

DomainKits MCP connects AI assistants (Claude, GPT, etc.) to professional domain intelligence tools. Instead of guessing domain availability, the AI can actually check it. Instead of generic naming suggestions, it validates ideas against real market data.

Shopify MCP Server

Enables interaction with Shopify store data through GraphQL API, providing tools for managing products, customers, orders, blogs, and articles.

Faraidh MCP Server

Enables Islamic inheritance law calculations (Faraidh) including heir validation, estate distribution, and handling special cases like Aul and Radd. Supports comprehensive inheritance scenarios with detailed reporting and case management functionality.

mcp-wisdom

Provides philosophical thinking frameworks and tools based on Stoic, cognitive, mindfulness, and strategic traditions to assist with decision-making and perspective. It enables AI models to apply structured wisdom from 2,500 years of tested frameworks to user problems.

Slack MCP Server

A FastMCP-based server that provides complete Slack integration for Cursor IDE, allowing users to interact with Slack API features using natural language.

Baby-SkyNet

Provides Claude AI with persistent, searchable memory management across sessions using SQL database, semantic analysis with multi-provider LLM support (Anthropic/Ollama), vector search via ChromaDB, and graph-based knowledge relationships through Neo4j integration.

HiveFlow MCP Server

Connects AI assistants (Claude, Cursor, etc.) directly to the HiveFlow automation platform, allowing them to create, manage, and execute automation flows through natural language commands.

Jokes MCP Server

An MCP server that allows Microsoft Copilot Studio to fetch random jokes from three sources: Chuck Norris jokes, Dad jokes, and Yo Mama jokes.

Usher MCP

Enables users to search and view detailed movie information from TMDB, including cast, ratings, and showtimes, through an interactive widget interface.

NHN Server MCP

Enables secure SSH access to servers through a gateway with Kerberos authentication, allowing execution of whitelisted commands with pattern-based security controls and server information retrieval.

amap-weather-server

MCP를 사용하는 amap-weather 서버

mcp_server

돌핀 MCP 클라이언트를 사용하여 샘플 MCP 서버를 구현하는 방법에 대한 안내입니다. **개요:** 이 가이드는 돌핀 MCP 클라이언트를 사용하여 간단한 MCP 서버를 구축하는 단계를 안내합니다. MCP (Minecraft Protocol)는 마인크래프트 클라이언트와 서버 간의 통신 프로토콜입니다. 이 샘플 서버는 기본적인 연결 수락, 핸드셰이크 처리, 그리고 간단한 상태 응답을 제공합니다. **필요 사항:** * **Python 3.6 이상:** 돌핀 MCP 클라이언트는 Python으로 작성되었습니다. * **돌핀 MCP 클라이언트 라이브러리:** `pip install dolphin-mcp`를 사용하여 설치합니다. * **네트워크 프로그래밍에 대한 기본적인 이해:** 소켓, 바이트 스트림 등에 대한 이해가 필요합니다. **구현 단계:** 1. **필요한 라이브러리 가져오기:** ```python import socket import struct import json from dolphin_mcp import packets from dolphin_mcp import utils ``` 2. **서버 설정:** ```python HOST = '127.0.0.1' # 로컬 호스트 PORT = 25565 # 마인크래프트 기본 포트 ``` 3. **소켓 생성 및 바인딩:** ```python server_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) server_socket.bind((HOST, PORT)) server_socket.listen(1) # 한 번에 하나의 연결만 허용 print(f"서버가 {HOST}:{PORT}에서 시작되었습니다.") ``` 4. **클라이언트 연결 수락:** ```python client_socket, client_address = server_socket.accept() print(f"{client_address}에서 연결이 수락되었습니다.") ``` 5. **핸드셰이크 처리:** ```python # 패킷 길이 읽기 packet_length_bytes = client_socket.recv(1) packet_length = struct.unpack('>B', packet_length_bytes)[0] # 패킷 데이터 읽기 packet_data = client_socket.recv(packet_length) # 핸드셰이크 패킷 파싱 handshake_packet = packets.HandshakePacket.from_bytes(packet_data) print(f"프로토콜 버전: {handshake_packet.protocol_version}") print(f"서버 주소: {handshake_packet.server_address}") print(f"서버 포트: {handshake_packet.server_port}") print(f"다음 상태: {handshake_packet.next_state}") next_state = handshake_packet.next_state ``` 6. **상태 요청 처리 (상태 1):** ```python if next_state == 1: # 상태 요청 패킷 받기 (길이 1바이트, 내용 0x00) status_request_length_bytes = client_socket.recv(1) status_request_length = struct.unpack('>B', status_request_length_bytes)[0] status_request_data = client_socket.recv(status_request_length) # 상태 응답 생성 status_response = { "version": { "name": "샘플 서버", "protocol": handshake_packet.protocol_version }, "players": { "max": 100, "online": 0, "sample": [] }, "description": { "text": "돌핀 MCP 샘플 서버" } } status_response_json = json.dumps(status_response) status_response_bytes = status_response_json.encode('utf-8') status_response_length = len(status_response_bytes) # 패킷 길이와 데이터 전송 response_packet = struct.pack('>B', status_response_length) + status_response_bytes client_socket.sendall(response_packet) # Ping 요청 처리 (선택 사항) ping_request_length_bytes = client_socket.recv(1) ping_request_length = struct.unpack('>B', ping_request_length_bytes)[0] ping_request_data = client_socket.recv(ping_request_length) ping_payload = struct.unpack('>q', ping_request_data)[0] # long 타입으로 언팩 # Ping 응답 생성 ping_response = struct.pack('>q', ping_payload) ping_response_length = len(ping_response) # 패킷 길이와 데이터 전송 ping_response_packet = struct.pack('>B', ping_response_length) + ping_response client_socket.sendall(ping_response_packet) ``` 7. **로그인 처리 (상태 2 - 구현하지 않음):** ```python elif next_state == 2: print("로그인 요청은 아직 구현되지 않았습니다.") # TODO: 로그인 처리 구현 ``` 8. **연결 종료:** ```python client_socket.close() server_socket.close() print("연결이 종료되었습니다.") ``` **전체 코드 예시:** ```python import socket import struct import json from dolphin_mcp import packets from dolphin_mcp import utils HOST = '127.0.0.1' PORT = 25565 server_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) server_socket.bind((HOST, PORT)) server_socket.listen(1) print(f"서버가 {HOST}:{PORT}에서 시작되었습니다.") client_socket, client_address = server_socket.accept() print(f"{client_address}에서 연결이 수락되었습니다.") # 핸드셰이크 packet_length_bytes = client_socket.recv(1) packet_length = struct.unpack('>B', packet_length_bytes)[0] packet_data = client_socket.recv(packet_length) handshake_packet = packets.HandshakePacket.from_bytes(packet_data) print(f"프로토콜 버전: {handshake_packet.protocol_version}") print(f"서버 주소: {handshake_packet.server_address}") print(f"서버 포트: {handshake_packet.server_port}") print(f"다음 상태: {handshake_packet.next_state}") next_state = handshake_packet.next_state if next_state == 1: # 상태 요청 status_request_length_bytes = client_socket.recv(1) status_request_length = struct.unpack('>B', status_request_length_bytes)[0] status_request_data = client_socket.recv(status_request_length) status_response = { "version": { "name": "샘플 서버", "protocol": handshake_packet.protocol_version }, "players": { "max": 100, "online": 0, "sample": [] }, "description": { "text": "돌핀 MCP 샘플 서버" } } status_response_json = json.dumps(status_response) status_response_bytes = status_response_json.encode('utf-8') status_response_length = len(status_response_bytes) response_packet = struct.pack('>B', status_response_length) + status_response_bytes client_socket.sendall(response_packet) # Ping 요청 ping_request_length_bytes = client_socket.recv(1) ping_request_length = struct.unpack('>B', ping_request_length_bytes)[0] ping_request_data = client_socket.recv(ping_request_length) ping_payload = struct.unpack('>q', ping_request_data)[0] ping_response = struct.pack('>q', ping_payload) ping_response_length = len(ping_response) ping_response_packet = struct.pack('>B', ping_response_length) + ping_response client_socket.sendall(ping_response_packet) elif next_state == 2: print("로그인 요청은 아직 구현되지 않았습니다.") client_socket.close() server_socket.close() print("연결이 종료되었습니다.") ``` **실행 방법:** 1. 위 코드를 `mcp_server.py`와 같은 파일로 저장합니다. 2. 터미널에서 `python mcp_server.py`를 실행합니다. 3. 마인크래프트 클라이언트를 실행하고, 서버 주소를 `127.0.0.1:25565`로 설정하여 연결합니다. **주의 사항:** * 이 코드는 매우 기본적인 샘플 서버이며, 실제 마인크래프트 서버의 모든 기능을 제공하지 않습니다. * 에러 처리, 보안, 성능 최적화 등은 추가적으로 구현해야 합니다. * 돌핀 MCP 클라이언트 라이브러리의 최신 문서를 참고하여 더 많은 기능을 활용할 수 있습니다. * `struct.pack`과 `struct.unpack`을 사용하여 바이트를 패킹/언패킹할 때, 바이트 순서(endianness)와 데이터 타입을 정확하게 지정해야 합니다. 위 예시에서는 `>` (big-endian)과 `B` (unsigned byte), `q` (long long)를 사용했습니다. **다음 단계:** * 로그인 처리 구현 * 채팅 기능 구현 * 플레이어 위치 정보 처리 * 청크 데이터 전송 * 더 많은 마인크래프트 프로토콜 패킷 처리 이 가이드가 돌핀 MCP 클라이언트를 사용하여 마인크래프트 서버를 구축하는 데 도움이 되기를 바랍니다. 궁금한 점이 있으면 언제든지 질문해주세요.

Wise MCP Server

Enables access to Wise API functionality for managing recipients and sending money transfers. Supports listing recipients, creating new recipients, validating account details, and executing money transfers with authentication handling.

Plex MCP Account Finder

Connects to multiple Plex accounts to perform fuzzy searches for users across servers by email, username, or display name, and generates authentication tokens for new account access.

Aviation Weather MCP Server

Provides real-time access to official aviation weather data including METARs, TAFs, and PIREPs directly from aviationweather.gov. It enables users to query airport observations, forecasts, and pilot reports through natural language within Claude.

macOS Ecosystem MCP Server

Provides secure access to macOS Reminders, Calendar, and Notes using semantic tools and validated AppleScript templates. It enables users to manage schedules, tasks, and notes through natural language while ensuring multi-layer security validation.

Sean-MCP

A GitHub integration tool that enables MCP clients to manage pull requests through tools for creating, updating, and listing PRs with automated descriptions. It also includes a webhook server for real-time PR updates and a customizable CLI with distinct personality modes.

Markdown to Card - MCP工具

A powerful MCP tool that converts Markdown documents into beautiful knowledge card images with 20+ card styles, suitable for sharing on blogs and social media.

USDA Nutrition Database MCP Server

Provides intelligent access to the USDA nutrition database through AI assistants, enabling users to search foods, compare nutritional content, find foods high in specific nutrients, and query authoritative nutrition data across 7,146+ food items through natural language.

yunxin-mcp-server

윤신-mcp-서버

MusicMCP.AI

Enables AI-powered music generation through natural language commands, supporting both inspiration mode (AI-generated lyrics and style) and custom mode (user-provided lyrics and parameters) to create songs with direct download links.

MCP OpenAPI Connector

Enables Claude Desktop and other MCP clients to interact with any OAuth2-authenticated OpenAPI-based API through automatic tool generation from OpenAPI specifications, with built-in token management and authentication handling.