Discover Awesome MCP Servers

daedalus

Enables driving a real Chrome instance remotely through MCP, including per-tab control, JavaScript evaluation, screenshots, cookie and network capture, and CDP fallback with token-based authentication.

Generate-Prd-Prompt

Mercury Spec Ops MCP Server is a dynamic prompt generation and template assembly tool based on a modular architecture. It is suitable for the interaction between AI assistants and professional content, and supports the dynamic generation of 31 technology stacks, 10 analysis dimensions and 34 templat

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.

oura-mcp

An MCP server that enables AI assistants to access Oura Ring health data including activity, sleep, heart rate, stress, and personal info.

mcp-housing-intel

Chains FRED, BLS, ATTOM, and HUD APIs to provide housing intelligence data through a single MCP server.

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.

dida-mcp-server

Enables AI assistants to manage TickTick/Dida365 tasks, projects, and tags through the MCP protocol, with features for GTD-based task organization and OAuth authentication.

ae-mcp

Enables AI assistants to operate Adobe After Effects with the dexterity of an editor: reading projects, creating and rigging layers, setting real velocity curves, animating text, building native SVG-based shapes, applying effects, expressions, masks, and viewing render snapshots to verify results.

Controtto

Okay, I understand. I can translate English text into Korean. Furthermore, I can analyze Go code and provide feedback based on Domain-Driven Design (DDD) and Clean Architecture principles. I will strive to be strict in my evaluation, looking for: * **Clear Domain Modeling:** Are the domain concepts well-defined and represented in the code? Are aggregates, entities, value objects, and domain services appropriately used? * **Ubiquitous Language:** Is the code using a consistent and understandable vocabulary that reflects the domain? * **Separation of Concerns:** Is the code properly layered, with a clear separation between the domain logic, application logic, infrastructure concerns (database, external APIs), and presentation layer? * **Dependency Inversion Principle (DIP):** Are high-level modules not dependent on low-level modules? Are abstractions used to decouple components? * **Testability:** Is the code designed in a way that makes it easy to write unit and integration tests? * **Clean Code Principles:** Is the code readable, maintainable, and well-documented? Are functions and methods small and focused? * **Hexagonal Architecture (Ports and Adapters):** Are the core domain logic and application services isolated from external dependencies through ports and adapters? **When you provide Go code, please also provide context:** * **What is the purpose of the code?** What problem is it trying to solve? * **What is the domain?** What are the key domain concepts? * **What are the architectural goals?** Are you aiming for a specific architecture (e.g., Hexagonal, Onion)? The more information you give me, the better I can assess the code against DDD and Clean Architecture principles. **Example:** You might provide code like this: ```go // User service for managing user accounts. package user import ( "database/sql" "fmt" ) type User struct { ID int Name string Email string } func CreateUser(db *sql.DB, name string, email string) error { _, err := db.Exec("INSERT INTO users (name, email) VALUES (?, ?)", name, email) if err != nil { return fmt.Errorf("failed to create user: %w", err) } return nil } func GetUser(db *sql.DB, id int) (*User, error) { row := db.QueryRow("SELECT id, name, email FROM users WHERE id = ?", id) user := &User{} err := row.Scan(&user.ID, &user.Name, &user.Email) if err != nil { return nil, fmt.Errorf("failed to get user: %w", err) } return user, nil } ``` And then ask: "This is a simple user service. The domain is user management. I'm trying to follow DDD principles. How well does this code adhere to DDD and Clean Architecture?" I would then analyze the code and provide feedback, such as: * **Domain Modeling:** The `User` struct is a good start, but it might be missing domain behavior. Consider adding methods to the `User` struct that encapsulate domain logic related to users (e.g., `ChangeEmail`, `Validate`). * **Separation of Concerns:** The `CreateUser` and `GetUser` functions directly interact with the database. This tightly couples the domain logic to the infrastructure. Consider introducing a repository interface to abstract away the database interaction. * **Dependency Inversion:** The `CreateUser` and `GetUser` functions depend directly on `*sql.DB`. This makes it difficult to test. Consider using an interface for the database connection. * **Ubiquitous Language:** The code uses terms like "user," "name," and "email," which are generally good. However, consider if there are more specific domain terms that could be used to make the code more expressive. I'm ready when you are. Please provide your code and context!

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.

Zignet

Enables AI-powered Zig programming assistance through code generation, debugging, and documentation explanation. Uses local LLM models to provide idiomatic Zig code creation and analysis capabilities.

MCP Google Server

A Model Context Protocol server that provides web search capabilities using Google Custom Search API and webpage content extraction functionality.

TechWord Translator MCP Server

Provides translation services for technical terms across English, Spanish, and German via MCP tools for search and translation.

CodeGuard MCP Server

Provides centralized security instructions for AI-assisted code generation by matching context-aware rules to the user's programming language and file patterns. It ensures generated code adheres to security best practices without requiring manual maintenance of instruction files across individual repositories.

bb-mcp-server

An MCP server for Bitbucket Cloud that enables reading and managing pull requests, comments, and descriptions via MCP clients.

Frappe Assistant Core

MCP server that enables LLMs to interact with ERPNext/Frappe sites for document CRUD, search, reports, workflows, and analytics, respecting user permissions and logging all actions.

SimpleMCP

A lightweight MCP server that auto-discovers tool kits, enabling tools like SQLite queries and web searches via Tavily API.

pendpost

Pendpost MCP server — exposes ~43 tools for posting, scheduling, and managing content via the Pendpost platform.

onbid-mcp

Enables LLM clients to ask plain-language questions about Korean public auction property data from the 온비드 OpenAPI, including normalized pricing, location, and failed-sale history.

Todo MCP Server

A multi-node todo application server using MCP protocol, Redis for storage, and OpenRouter for AI-powered prioritization analysis.

market-recap

Provides a one-call snapshot of recent market activity and events.

ShortsMonkey MCP

A read-only MCP server for discovering YouTube outliers, analyzing viral Shorts, and evaluating single-video performance using stored snapshots.

Sentry MCP Server

Enables comprehensive Sentry monitoring including performance analysis, issue tracking, and transaction tracing.

spd-mcp

Enables remote control of Siglent SPD3303X DC power supplies via SCPI over TCP/IP, supporting output control, measurement, timers, and network configuration.

mcp-searxng-tool

AI 에이전트가 SearXNG 서비스를 통해 외부 웹사이트 콘텐츠와 정보를 검색할 수 있도록 하는 MCP 서버입니다.

text2img-mcp

Creates AI-generated images from text prompts using Google Gemini API, supporting business use cases like proposals, infographics, and charts.

domain-checker-mcp

Enables fast domain availability checking via hybrid DNS and RDAP/WHOIS verification, with support for bulk queries and automatic name expansion across popular TLDs.

EasyPlaywrightMCP

Enables automated testing and demo video creation using Playwright, with login, session orchestration, narration, and video compilation.

mcp-mysql-remote

Remote read-only MCP server that exposes diagnostic SQL queries to EasyJur's MySQL for Claude.ai via HTTPS, secured with OAuth 2.1 and PKCE.

Mercantry MCP Server

Enables AI agents to search and retrieve structured merchant data, check availability, manage bookings, and submit feedback against an open commerce registry with real restaurant data for LA, Hong Kong, and Tokyo.