Discover Awesome MCP Servers
Extend your agent with 57,384 capabilities via MCP servers.
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Slack MCP Server with SSE Transport
Slack MCP Server dengan transportasi SSE
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.
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.
Rideshare Comparison MCP
Compare Uber and Lyft prices for any route, get supported cities, and retrieve booking links using Claude Desktop.
pendpost
Pendpost MCP server — exposes ~43 tools for posting, scheduling, and managing content via the Pendpost platform.
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.
GeoRanker MCP Server
An agent-friendly MCP server for the GeoRanker High-Volume API, enabling SEO rank tracking and keyword management through natural language.
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.
Coval MCP Server
Enables AI assistants to interact with Coval's evaluation platform for launching and monitoring evaluation runs, managing agents and test sets, and retrieving evaluation metrics.
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.
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.
capacitor-stack
MCP server for building React + Capacitor + Tailwind + Konsta applications, providing tools for UI snippets, plugin management, and stack recommendations.
micropub-mcp
Enables AI agents to create, update, delete, and query posts on any Micropub-compatible blog with IndieAuth authentication.
Google News MCP Agent
Fetches news articles from Google News, vectorizes them locally using ChromaDB, and enables semantic search through natural language queries.
ZMCPTools
A multi-agent orchestration platform for Claude Code providing 61 tools for autonomous agent coordination, browser automation, and documentation intelligence. It features LanceDB-powered semantic search, knowledge graph memory systems, and advanced task management for complex development workflows.
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.
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.
influx-mcp
MCP server for InfluxDB 2.x, tuned for Home Assistant long-term storage, enabling reading sensor history, finding anomalies, and running Flux queries.
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.
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.
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.
CustomerOS MCP Server
A local MCP server for managing CustomerOS tickets, accounts, team members, and notes, backed by Supabase.