Discover Awesome MCP Servers
Extend your agent with 28,614 capabilities via MCP servers.
- All28,614
- Developer Tools3,867
- Search1,714
- Research & Data1,557
- AI Integration Systems229
- Cloud Platforms219
- Data & App Analysis181
- Database Interaction177
- Remote Shell Execution165
- Browser Automation147
- Databases145
- Communication137
- AI Content Generation127
- OS Automation120
- Programming Docs Access109
- Content Fetching108
- Note Taking97
- File Systems96
- Version Control93
- Finance91
- Knowledge & Memory90
- Monitoring79
- Security71
- Image & Video Processing69
- Digital Note Management66
- AI Memory Systems62
- Advanced AI Reasoning59
- Git Management Tools58
- Cloud Storage51
- Entertainment & Media43
- Virtualization42
- Location Services35
- Web Automation & Stealth32
- Media Content Processing32
- Calendar Management26
- Ecommerce & Retail18
- Speech Processing18
- Customer Data Platforms16
- Travel & Transportation14
- Education & Learning Tools13
- Home Automation & IoT13
- Web Search Integration12
- Health & Wellness10
- Customer Support10
- Marketing9
- Games & Gamification8
- Google Cloud Integrations7
- Art & Culture4
- Language Translation3
- Legal & Compliance2
BMAD Agent FastMCP Service
A professional AI agent system that provides 10+ specialized agents and 25+ MCP tools to support development workflows in Cursor IDE, with dual LLM mode support (built-in and DeepSeek API).
adops-mcp
Cross-platform ad management MCP server for Google Ads and Meta Ads. Campaign analytics, A/B testing with z-test, anomaly detection, and budget reallocation. 15 tools, 60 tests.
Salesforce MCP
Enables interaction with Salesforce API using jsforce, allowing users to query and manage Salesforce data through the Model Context Protocol with username/password authentication.
Simple Timer MCP Server
An MCP server that provides interval timing functionality using token-based time tracking, allowing users to start timers with unique identifiers and check elapsed time in milliseconds or human-readable format.
qdrant-mcp-local
Aqui está uma configuração Docker Compose para iniciar facilmente o Qdrant e o MCP-server-qdrant em um ambiente local: ```yaml version: "3.9" services: qdrant: image: qdrant/qdrant:latest ports: - "6333:6333" # Porta para a API do Qdrant - "6334:6334" # Porta para gRPC volumes: - qdrant_data:/qdrant/storage # Persistência de dados (opcional) restart: unless-stopped mcp-server-qdrant: image: your-mcp-server-qdrant-image:latest # Substitua pela sua imagem do MCP-server-qdrant ports: - "8000:8000" # Porta para a API do MCP-server-qdrant (ajuste conforme necessário) environment: QDRANT_HOST: qdrant QDRANT_PORT: 6333 # Adicione outras variáveis de ambiente necessárias para o seu MCP-server-qdrant depends_on: - qdrant restart: unless-stopped volumes: qdrant_data: # Volume para persistir os dados do Qdrant (opcional) ``` **Explicação:** * **`version: "3.9"`:** Especifica a versão do Docker Compose. * **`services:`:** Define os serviços que serão executados. * **`qdrant:`:** Define o serviço Qdrant. * **`image: qdrant/qdrant:latest`:** Usa a imagem mais recente do Qdrant do Docker Hub. * **`ports:`:** Mapeia as portas do container para o host. `6333` é a porta padrão para a API do Qdrant e `6334` para gRPC. * **`volumes:`:** Monta um volume para persistir os dados do Qdrant. Isso é opcional, mas recomendado para evitar a perda de dados ao reiniciar o container. * **`restart: unless-stopped`:** Reinicia o container automaticamente, a menos que ele tenha sido parado manualmente. * **`mcp-server-qdrant:`:** Define o serviço MCP-server-qdrant. * **`image: your-mcp-server-qdrant-image:latest`:** **IMPORTANTE:** Substitua `your-mcp-server-qdrant-image:latest` pelo nome da sua imagem Docker do MCP-server-qdrant. * **`ports:`:** Mapeia a porta do container para o host. `8000` é um exemplo, ajuste conforme a porta que seu MCP-server-qdrant usa. * **`environment:`:** Define variáveis de ambiente para o container. * **`QDRANT_HOST: qdrant`:** Define o hostname do Qdrant. Como estamos usando o Docker Compose, podemos usar o nome do serviço (`qdrant`) como hostname. * **`QDRANT_PORT: 6333`:** Define a porta da API do Qdrant. * **Adicione outras variáveis de ambiente:** Seu MCP-server-qdrant pode precisar de outras variáveis de ambiente, como chaves de API, configurações de banco de dados, etc. Adicione-as aqui. * **`depends_on:`:** Garante que o Qdrant seja iniciado antes do MCP-server-qdrant. * **`restart: unless-stopped`:** Reinicia o container automaticamente, a menos que ele tenha sido parado manualmente. * **`volumes:`:** Define os volumes que serão usados. * **`qdrant_data:`:** Define um volume nomeado para persistir os dados do Qdrant. **Como usar:** 1. **Salve o código acima em um arquivo chamado `docker-compose.yml`.** 2. **Substitua `your-mcp-server-qdrant-image:latest` pelo nome da sua imagem Docker do MCP-server-qdrant.** 3. **Adicione as variáveis de ambiente necessárias para o seu MCP-server-qdrant na seção `environment`.** 4. **Abra um terminal no mesmo diretório do arquivo `docker-compose.yml`.** 5. **Execute o comando `docker-compose up -d`.** Isso irá baixar as imagens, criar os containers e iniciá-los em modo detached (em segundo plano). **Para parar os containers:** Execute o comando `docker-compose down`. **Observações:** * **Persistência de dados:** O volume `qdrant_data` é usado para persistir os dados do Qdrant. Se você não precisar persistir os dados, você pode remover a seção `volumes` do serviço `qdrant` e a definição do volume `qdrant_data`. * **Variáveis de ambiente:** Certifique-se de configurar corretamente as variáveis de ambiente para o seu MCP-server-qdrant. * **Portas:** Ajuste as portas conforme necessário. * **Imagem do MCP-server-qdrant:** Lembre-se de substituir `your-mcp-server-qdrant-image:latest` pelo nome da sua imagem Docker. * **Rede:** O Docker Compose cria uma rede padrão para os containers, permitindo que eles se comuniquem usando seus nomes de serviço como hostnames. Este é um exemplo básico. Você pode precisar ajustar a configuração para atender às suas necessidades específicas. Consulte a documentação do Qdrant e do MCP-server-qdrant para obter mais informações.
ABP.IO MCP Server
Enables AI models to interact with ABP.IO applications through over 48 tools for managing modules, entities, users, and multi-tenancy. It supports comprehensive application lifecycle management and automated UI generation across multiple frameworks including Angular, Blazor, and MVC.
Remote MCP Server on Cloudflare
A Model Context Protocol server that runs on Cloudflare Workers with OAuth login, allowing clients like Claude Desktop to connect to it for tool-augmented AI interactions.
MCP-Demo
MCP Duty Pharma
MCP Duty Pharma
Wan2GP MCP Server
Enables AI assistants to generate videos from text prompts and images by interfacing with a Wan2GP Gradio server. It provides tools for high-quality video generation, queue management, and model discovery through the Model Context Protocol.
mcp-tts-server
CODING DevOps MCP Server
Implementa o Protocolo de Contexto do Modelo (MCP) para permitir a interação com a plataforma CODING DevOps através de interfaces padronizadas para gerenciar projetos e itens de trabalho.
mcp-superset
Full-featured MCP server for Apache Superset — 135+ tools for dashboards, charts, datasets, SQL Lab, security (users, roles, RLS, groups), audit, and more. Built-in safety validations.
stockmarketscan/mcp-server
18 tools for US stock screeners, chart patterns, options flow signals and equities research. Hosted SSE transport mcp.stockmarketscan.com with BYOK authentication.
MacOS Clipboard MCP Server
Provides AI assistants access to the macOS clipboard content, supporting text, images, and binary data via OSAScript.
Port MCP Server
Espelho de
Full-Stack MCP Server
Provides 8 specialized AI agents (Frontend, Backend, Database, API, DevOps, Testing, Security, Performance) for full-stack web development, powered by high-speed Cerebras inference and integrated with OpenCode CLI.
Readwise MCP Enhanced
A comprehensive MCP server that unifies Readwise Reader document management with full Readwise highlights functionality, featuring AI-powered text processing and 94% reduction in token usage. Enables saving, searching, and managing documents and highlights through natural language with advanced content controls and spaced repetition learning.
SQL-Transpiler MCP Tool
Converts SQL queries between different database dialects using the sqlglot library to ensure cross-system compatibility. It allows users to list supported dialects and transpile SQL code from one syntax to another through the Model Context Protocol.
MCP Server Template
A scaffold project for building FastAPI-based Model Context Protocol servers with automatic tool discovery and router capabilities.
Uber MCP Server
Enables AI assistants to interact with the Uber API for ride management, including requesting rides, obtaining price and time estimates, and tracking active trip status. It supports comprehensive journey features such as viewing ride history, cancelling requests, and rating drivers through a secure OAuth 2.0 integration.
Honeycomb MCP Server
Espelho de
MCP Calculator Project
A communication pipe and tool suite that enables AI models to interact with external systems through mathematical calculations, remote control, and data processing. It supports multiple transport protocols including stdio, SSE, and HTTP for flexible and extensible tool integration.
Obsidian MCP
Um servidor de Protocolo de Contexto de Modelo que permite que assistentes de IA leiam, escrevam e manipulem notas no seu cofre do Obsidian através de uma interface padronizada.
MCP Worktree Voting Server
Enables parallel implementation of tasks using git worktrees, allowing you to create multiple variants of a solution, evaluate them side-by-side, and select the best one.
Simple TypeScript MCP Server
A TypeScript template for building Model Context Protocol servers that implements basic note-taking CRUD operations with JSON responses.
MCP Database Tools Server
An MCP server designed to automate Django database setup and management, including PostgreSQL database creation and extension configuration. It enables users to update environment files and execute Django management commands through integrated tools like VS Code Copilot.
yutu
A fully functional MCP server and CLI for YouTube to automate YouTube operation.
TA-Lib MCP Server
Provides technical analysis indicators like SMA, EMA, RSI, MACD, Bollinger Bands, and Stochastic through MCP, enabling AI assistants to perform financial market analysis and calculations on price data.
Phabricator MCP Server
Enables AI assistants to interact with Phabricator for task management and code review workflows, including viewing and commenting on tasks, managing differential revisions, and providing intelligent review analysis with code context.