Discover Awesome MCP Servers

OpenGenes MCP Server

Provides standardized access to aging and longevity research data from the OpenGenes database, enabling AI assistants to query comprehensive biomedical datasets through SQL and structured interfaces.

mcp-searxng-tool

一个用于让 AI Agent 通过 SearXNG 服务来搜索外部网站内容和信息的 MCP 服务器。

Notes MCP

An MCP server that enables AI assistants like Claude to access and manipulate Apple Notes on macOS, allowing for retrieving, creating, and managing notes through natural language interactions.

Brewfather Mcp

MCP 服务器访问 Brewfather

Index Network MCP Server

Enables ChatGPT integration with Index Network's discovery protocol through MCP tools. Provides quick setup with ngrok tunneling for public access and includes health check, echo, and search functionality.

ms-sentinel-mcp-server

ms-sentinel-mcp-server

MCP GitLab Server

Enables comprehensive GitLab integration allowing LLMs to manage projects, issues, merge requests, repository files, CI/CD pipelines, and perform batch operations. Supports advanced features like AI-optimized summaries, smart diffs, and atomic operations with rollback support.

SQL Server Analysis Services MCP Server by CData

SQL Server Analysis Services MCP Server by CData

Controtto

Okay, I understand. I will do my best to translate English text into Chinese, and when presented with Go code, I will attempt to analyze it from the perspective of Domain-Driven Design (DDD) and Clean Architecture principles. **Specifically, when analyzing Go code, I will look for:** * **DDD Aspects:** * **Ubiquitous Language:** Is the code using terminology that aligns with the business domain? Are the names of variables, functions, and types meaningful to domain experts? * **Entities:** Are there well-defined entities with identity and behavior? * **Value Objects:** Are there immutable value objects representing domain concepts? * **Aggregates:** Are aggregates used to enforce consistency and manage transactions? Are aggregate roots clearly defined? * **Domain Services:** Are domain services used to encapsulate complex domain logic that doesn't naturally belong to an entity or value object? * **Repositories:** Are repositories used to abstract data access and persistence? * **Domain Events:** Are domain events used to decouple different parts of the system and react to changes in the domain? * **Bounded Contexts:** (If applicable) Is the code organized into bounded contexts with clear boundaries and responsibilities? * **Clean Architecture Aspects:** * **Dependency Inversion Principle (DIP):** Are high-level modules not dependent on low-level modules? Are abstractions used to decouple layers? * **Interface Segregation Principle (ISP):** Are interfaces small and focused, avoiding unnecessary dependencies? * **Single Responsibility Principle (SRP):** Do classes/modules have a single, well-defined responsibility? * **Layers:** Are there distinct layers (e.g., presentation, application, domain, infrastructure)? * **Use Cases/Interactors:** Are use cases clearly defined and implemented as interactors? * **Entities (Domain Layer):** Is the core business logic (entities and domain rules) independent of frameworks and infrastructure? * **Frameworks & Drivers (Outer Layer):** Are frameworks and infrastructure concerns kept separate from the core business logic? * **Testability:** Is the code easily testable, with clear separation of concerns? **My analysis will be strict and critical.** I will point out potential violations of these principles and suggest improvements. I will also consider the trade-offs involved in applying these principles, as strict adherence is not always practical or beneficial. **Important Considerations:** * **Context is Key:** My analysis will be limited by the information you provide. The more context you give me about the domain, the requirements, and the overall architecture, the better I can assess the code. * **Subjectivity:** DDD and Clean Architecture are not rigid rules, but rather guidelines. There is room for interpretation and different approaches. My analysis will reflect my understanding of these principles, which may differ from yours. * **Code Completeness:** I can only analyze the code you provide. I cannot infer the entire system architecture or domain model from a small snippet. **Example:** If you provide me with the following Go code: ```go package main import "fmt" type User struct { ID int Name string Email string } func SaveUser(db *sql.DB, user User) error { _, err := db.Exec("INSERT INTO users (name, email) VALUES (?, ?)", user.Name, user.Email) return err } func main() { // ... database connection ... user := User{Name: "John Doe", Email: "john.doe@example.com"} err := SaveUser(db, user) if err != nil { fmt.Println("Error saving user:", err) } } ``` I might respond with something like: "This code has several potential issues from a DDD and Clean Architecture perspective: * **Lack of Domain Layer:** The `User` struct is directly coupled to the database. It should be part of a dedicated domain layer, separate from infrastructure concerns. * **Anemic Domain Model:** The `User` struct only contains data and lacks behavior. Consider adding methods to the `User` struct that encapsulate domain logic related to users. * **Direct Database Access:** The `SaveUser` function directly interacts with the database. This violates the Dependency Inversion Principle. A repository interface should be used to abstract data access. * **Missing Repository:** There is no repository interface or implementation to handle user persistence. * **No Use Case:** The `main` function directly calls the `SaveUser` function. This should be encapsulated in a use case or interactor. To improve this code, consider: 1. Creating a `domain` package with the `User` entity and any related value objects. 2. Defining a `UserRepository` interface in the `domain` package. 3. Implementing the `UserRepository` interface in an `infrastructure` package, using a database connection. 4. Creating an `application` package with a `CreateUser` use case that uses the `UserRepository` to persist the user. This would result in a more decoupled, testable, and maintainable codebase that adheres to DDD and Clean Architecture principles." **Now, please provide me with the text you want me to translate or the Go code you want me to analyze.**

Aseprite MCP Tools

A Python MCP server enabling programmatic interaction with Aseprite for pixel art creation and manipulation with features like drawing operations, palette management, and batch processing.

JEFit MCP Server

Enables analysis and retrieval of JEFit workout data through natural language. Provides access to workout dates, detailed exercise information, and batch workout analysis for fitness tracking and progress monitoring.

Asana MCP Server

An MCP (Multi-Agent Conversation Protocol) server that enables interacting with the Asana API through natural language commands for task management, project organization, and team collaboration.

MCP API Server

A Model Context Protocol server that enables AI assistants to make HTTP requests (GET, POST, PUT, DELETE) to external APIs through standardized MCP tools.

MCP Server with External Tools

Enables AI models to access external services including weather data, file system operations, and SQLite database interactions through a standardized JSON-RPC interface. Features production-ready architecture with security, rate limiting, and comprehensive error handling.

Alibaba Cloud DMS MCP Server

A Model Context Protocol server that enables large language models to access database metadata and perform cross-engine data querying across diverse database ecosystems.

Cyber Sentinel MCP Server

A threat intelligence aggregation server that provides unified access to multiple security sources for analyzing indicators (IPs, domains, hashes, URLs) with confidence scoring.

Confluence MCP Server

镜子 (jìng zi)

JP's MCP Collection

A comprehensive utility MCP server that enables AI assistants to execute system commands, manage files, integrate with Google Sheets and Tasks, perform AI-powered text processing, and load dynamic prompts from markdown files.

Firecrawl MCP Server

一个模型上下文协议服务器，它使 AI 助手能够通过 Firecrawl API 执行高级网络抓取、爬行、搜索和数据提取。

Omise MCP Server

Enables comprehensive payment processing through Omise APIs including charges, customers, transfers, refunds, disputes, recurring payments, and webhooks. Provides 51 tools covering all Omise API functionality for secure payment integration.

sqlite-kg-vec-mcp

基于 SQLite 的，集成了知识图谱和向量数据库的 MCP 服务器

Act-On MCP Server by CData

This read-only MCP Server allows you to connect to Act-On data from Claude Desktop through CData JDBC Drivers. Free (beta) read/write servers available at https://www.cdata.com/solutions/mcp

Repo Explorer

MCP服务器，通过高级缓存实现高效的Git仓库探索。跨多个仓库搜索代码模式，管理参考代码库，并分析模式，性能提升95%以上。通过桌面应用程序或VSCode扩展与Claude AI集成。可配置且平台无关。

Test MCP Server

A simple learning-focused MCP server that demonstrates basic functionality with tools for mathematical operations, system information, and email validation, plus sample file resources. Perfect for understanding MCP protocol basics and testing integrations.

Remote MCP Server Authless

A serverless deployment for Model Context Protocol server on Cloudflare Workers without authentication requirements, enabling users to create custom AI tools accessible via Cloudflare AI Playground or Claude Desktop.

MCP Containers

数百个 MCP 服务器的容器化版本 📡 🧠