Discover Awesome MCP Servers

smart-terminal-mcp

A PTY-based MCP server providing persistent, interactive shell sessions with strong Windows support, enabling AI agents to run commands, handle interactive tools, and manage large output across MCP-compatible clients.

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

Server Protokol Konteks Model yang memungkinkan asisten AI untuk melakukan web scraping, crawling, pencarian, dan ekstraksi data tingkat lanjut melalui API Firecrawl.

CityJS London 2026 Companion

An MCP server that renders rich HTML widgets directly in ChatGPT for conference information. It provides schedule, speakers, and talk search functionality with themed UI components.

bilibili-subtitle-fetch

A Bilibili subtitle fetching MCP server that supports various input formats (BV number, video URL, short link) and offers configurable language preferences, output formats, and ASR fallback.

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.

Amazon SP-API MCP Server

Enables natural language exploration and execution of Amazon Selling Partner API operations, with automatic parameter validation, code generation, and OAuth2 token management.

Civis MCP Server

Enables interaction with the Civis Platform for data exploration, querying, and workflow execution. Supports schema-restricted read-only mode and tools like run_query, list_tables, and publish_html_report.

Confluence MCP Server

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instantKOM MCP Server

Enables AI assistants to manage instantKOM messenger platform resources (channels, contacts, messages, newsletters, bots, flows, analytics) via structured type-safe tool calls.

Slice.js Documentation MCP

Enables AI assistants to search, list, and retrieve documentation from the Slice.js official GitHub repository. It provides full-text search capabilities and can deliver individual doc pages or a complete documentation bundle for comprehensive LLM context.

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.

shipcheck-mcp

Enables AI agents to run Shipcheck on local JavaScript/TypeScript repositories, scanning for launch risks like exposed env vars, unsigned webhooks, and missing security guardrails.

Controtto

Okay, I understand. I can translate English text to Indonesian. Furthermore, I can analyze Go code and evaluate it based on Domain-Driven Design (DDD) and Clean Architecture principles. I will strive to be strict in my assessment, looking for adherence to the following: **Domain-Driven Design (DDD):** * **Ubiquitous Language:** Is there a clear and consistent language used throughout the code and documentation that reflects the domain? * **Bounded Contexts:** Are the boundaries of different domain areas clearly defined and separated? Are there explicit integration points between contexts? * **Entities:** Are entities properly modeled with identity, attributes, and behavior relevant to the domain? * **Value Objects:** Are value objects immutable and used to represent concepts without identity? * **Aggregates:** Are aggregates used to enforce consistency and transactional boundaries within the domain? Is there a clear aggregate root? * **Repositories:** Are repositories used to abstract data access and persistence details from the domain logic? * **Domain Services:** Are domain services used to encapsulate complex domain logic that doesn't naturally belong to an entity or value object? * **Domain Events:** Are domain events used to decouple different parts of the system and react to changes in the domain? **Clean Architecture:** * **Independence of Frameworks:** Is the core business logic independent of specific frameworks, databases, or UI technologies? * **Testability:** Is the code easily testable, with clear separation of concerns and dependencies? * **Independence of UI:** Can the UI be changed without affecting the core business logic? * **Independence of Database:** Can the database be changed without affecting the core business logic? * **Independence of External Agencies:** Can external services or APIs be changed without affecting the core business logic? * **Dependency Rule:** Dependencies should only point inwards. Inner layers (e.g., Entities, Use Cases) should not depend on outer layers (e.g., Infrastructure, UI). * **Layers:** Are the layers of the architecture clearly defined and separated (e.g., Entities, Use Cases, Interface Adapters, Frameworks & Drivers)? * **Use Cases (Interactors):** Are use cases clearly defined and encapsulate the application's business rules? * **Entities:** Do the entities represent the core business concepts and rules? * **Interface Adapters:** Are interface adapters responsible for converting data between the format most convenient for the use cases and entities, and the format most convenient for some external agency such as the Database or the Web. * **Frameworks and Drivers:** This layer is composed of all the frameworks and tools you’re using. **In my analysis, I will look for:** * **Code Structure:** How well the code is organized into packages and modules. * **Naming Conventions:** Whether the naming is clear, consistent, and reflects the domain. * **Error Handling:** How errors are handled and propagated. * **Test Coverage:** The extent and quality of unit and integration tests. * **Coupling and Cohesion:** How tightly coupled the different parts of the system are, and how well each module focuses on a single responsibility. * **Maintainability:** How easy the code is to understand, modify, and extend. **To get the best results, please provide me with:** * **The Go code you want me to analyze.** * **A brief description of the domain the code is intended to model.** * **Any specific concerns or areas you'd like me to focus on.** I will do my best to provide a thorough and helpful assessment based on these principles. I will also try to explain my reasoning and suggest improvements where possible. Keep in mind that DDD and Clean Architecture are not silver bullets, and there are always trade-offs to consider.

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.

micropub-mcp

Enables AI agents to create, update, delete, and query posts on any Micropub-compatible blog with IndieAuth authentication.

LSP MCP Server for Rell

An MCP server for interacting with the Rell Language Server Protocol interface. It enables LLMs to query LSP Hover and Completion providers for Rell projects.

Google News MCP Agent

Fetches news articles from Google News, vectorizes them locally using ChromaDB, and enables semantic search through natural language queries.

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.

GeoRanker MCP Server

An agent-friendly MCP server for the GeoRanker High-Volume API, enabling SEO rank tracking and keyword management through natural language.

Jira & Confluence MCP Server

Enables interaction with Jira and Confluence APIs to search, create, and manage issues, pages, comments, and attachments across both Atlassian platforms.

Remote MCP Server (Authless)

A template for deploying authentication-free MCP servers on Cloudflare Workers. Enables quick deployment of custom tools accessible via SSE from MCP clients like Claude Desktop or Cloudflare AI Playground.

workday-mcp

Read-only MCP server for Workday that fetches your tasks and data cards (pay, benefits, compensation) via your existing browser session, returning structured JSON.

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.

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

MCP Atlassian

A Model Context Protocol server for Atlassian Jira and Confluence that supports both Cloud and On-Prem/Data Center deployments. It enables AI assistants to search, create, and manage issues and pages using secure authentication methods like PAT and OAuth.

Agentic Vault

MCP server that lets AI agents call APIs without ever seeing the credentials, using a local encrypted vault and per-secret allowlist policies for HTTP requests and subprocess environment variables.

SQL Server Analysis Services MCP Server by CData

SQL Server Analysis Services MCP Server by CData

oura-mcp

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