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The Figma MCP Server is a Model Context Protocol (MCP) server that provides Cursor with access to Figma files. It simplifies and translates Figma API responses, offering only the most relevant layout and styling information, which enhances AI accuracy in generating code from design data. This tool allows developers to fetch and implement Figma design metadata directly into code, improving productivity and accuracy compared to traditional methods. Developers and teams using Cursor as an AI coding assistant can benefit from this integration, streamlining the design-to-code process. The Figma MCP Server can be used locally or integrated into development environments, connecting to Cursor via HTTP mode and working seamlessly with tools like npm, pnpm, yarn, and bunx. Setting it up is particularly useful during early UI development or when design updates are frequent.

Crew AI MCP Server is an advanced MCP server that leverages the CrewAI framework to provide robust AI agent and task management capabilities. It simplifies the creation and management of AI agents, allowing users to define roles, goals, and tasks, and execute workflows seamlessly. This tool is ideal for developers, researchers, and organizations looking to automate and streamline processes, especially in Python-based environments and with OpenAI APIs. Supported on macOS, Linux, and Windows (via Git Bash), it requires Python 3.8 or higher, jq, and VSCode with the Roo Cline extension. Use Crew AI MCP Server to manage complex workflows, assign and monitor tasks, and enhance research and data analysis efforts.

The AWS Well-Architected Framework MCP Server is a project that provides an MCP (Model Context Protocol) server, offering guidance based on the six pillars of the AWS Well-Architected Framework: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability. This server allows users to interact with these principles programmatically via specific endpoints. It helps developers and architects evaluate their architecture against AWS best practices by providing detailed recommendations and tools like architecture analysis and review templates. Designed for cloud architects, developers, DevOps engineers, and IT professionals, it can be deployed locally or in any environment supporting Python 3.10 or higher. The server runs as an HTTP service on port 3001, making it accessible via API calls. It is particularly useful during the planning, development, and review phases of AWS architectures.

MCP Server is a server instance or system designed for hosting, cloud services, or managing computational tasks. Its specific purpose and functionality are not fully defined in the provided information. MCP Server is typically used for hosting applications, managing network resources, or facilitating cloud-based solutions, though the exact use case can vary. It can be deployed on-premises, in a data center, or on cloud infrastructure. The users of MCP Server may include IT professionals, developers, and organizations seeking scalable server solutions. The relevance of MCP Server depends on the specific needs of an organization or individual. Further details about its features, deployment, and unique selling points would provide a clearer understanding of its capabilities.

Elasticsearch MCP Server is a Model Context Protocol (MCP) server implementation designed to interact with Elasticsearch. It simplifies Elasticsearch operations by providing tools for index, document, and cluster management. Users can list indices, retrieve mappings, search documents using Query DSL, and check cluster health and statistics. This tool is beneficial for developers, data engineers, and DevOps professionals, especially those integrating natural language commands via platforms like Claude Desktop. The server can be run locally or in a Docker environment and is open-source under the Apache License Version 2.0.

Smart Photo Journal MCP Server is a specialized server designed to help users search and analyze their photo libraries with powerful tools. It supports features like location-based search, label-based search, people search, photo analysis, and fuzzy matching for flexible queries. The server integrates with macOS Photos library and operates locally, ensuring data privacy. Ideal for photographers, families, and travelers, it simplifies the process of managing and retrieving photos. Users can gain insights into their photography habits, making it perfect for events like family gatherings and vacations. To install, clone the repository, install dependencies, and configure the server using `claude_desktop_config.json`. Prerequisites include macOS with a Photos library and `uv` for dependency management.

mcp-tung-shing is a Model Context Protocol (MCP) service that provides detailed Chinese Traditional Almanac (Tung Shing) information. It offers features such as auspicious and inauspicious times, suitable and unsuitable activities, and conversions between Gregorian and Lunar calendars. This service is ideal for event planning and understanding cultural practices, supporting modern development workflows via NPX or CLI. Maintained by baranwang, the source code and documentation are available on GitHub under the repository baranwang/mcp-tung-shing. The latest update was made on January 21, 2025. For integration, use either the NPX method or CLI, and the primary API endpoint is 'get-tung-shing', which accepts 'startDate' and 'days' parameters.

The web-browser-mcp-server is a lightweight Minimum Control Program (MCP) server designed to provide web browsing capabilities. It leverages BeautifulSoup4, a Python library for parsing HTML and XML documents, to interact with web content. This tool is ideal for developers who need a streamlined solution for automating web interactions, scraping, or other browser-based tasks without the overhead of full-fledged browsers. It is particularly beneficial for developers, data scientists, and engineers working on web scraping, automated testing, or headless browsing. The project is available on GitHub at https://github.com/blazickjp/web-browser-mcp-server. Consider using this server when your project requires lightweight web-browsing functionality, such as scraping specific web pages, automating simple HTTP requests, or handling static content extraction. While it does not directly influence SEO, it can be used in tools that analyze or improve SEO metrics. Note that it may not fully render JavaScript-heavy websites, so for such cases, tools like Puppeteer or Selenium might be more suitable.

Remote-MCP Server is a type-safe and bidirectional solution for remote Model Context Protocol (MCP) communication. It enables a local MCP client to connect to a remote MCP server, facilitating centralized management of model contexts. Created to meet immediate needs for remote access, it serves as an interim solution until the official MCP support is released in Q1 2025. Developers and organizations requiring immediate remote MCP functionalities can benefit from this library. Remote-MCP Server can be deployed on platforms like Cloudflare Workers and Node.js, with integrations for Nest.js. Currently in active development, its initial release (v0.1.0) is available, and future updates are expected. Core features include type-safe communication, basic MCP commands, crash-safe handling, event subscription, and authentication middleware. Contributions are welcome, and the project is licensed under the MIT License.

MCP Server Starter is a production-ready template for building Model Context Protocol (MCP) servers using TypeScript. It provides a clean, maintainable project structure and integrates tools like Bun for fast development, Biome for linting, and standard-version for automated version management. This template is ideal for developers aiming to build MCP servers efficiently, especially for environments like Claude Desktop. Maintained by StevenStavrakis on GitHub, it simplifies the process of creating, testing, and publishing MCP servers. Use MCP Server Starter when starting a new MCP server project to ensure robust structure and tooling.

The tavily-search-mcp-server is an MCP server implementation that integrates the Tavily Search API to provide optimized search capabilities for Large Language Models (LLMs). It supports web search, content extraction, domain filtering, and optional inclusion of images, image descriptions, short answers, and raw HTML content. This server enhances search functionality by offering tailored results, allowing users to control search depth, topics, time ranges, and domains. It is particularly useful for integrating advanced search capabilities into applications like Claude Desktop. Developers and organizations working with LLMs or requiring enhanced search can benefit from this tool. The server can be run locally via Node.js (npm) or Docker and integrates seamlessly with Claude Desktop. To set it up, clone the repository, install dependencies, and configure it in the `mcpServers` object. Prerequisites include Claude Desktop, a Tavily API key, and either Node.js/npm or Docker.

Bear MCP Server is a Model Context Protocol (MCP) server that provides programmatic access to notes stored in the Bear Notes application. It runs SQL commands on the SQLite database where Bear stores its notes, enabling users to read, search, and list tags. This tool is ideal for developers, power users, or anyone looking to automate tasks, integrate with other applications, or build custom tools around their Bear Notes data. Operating on macOS systems, Bear MCP Server requires Node.js and the Bear application. When the server starts, it offers MCP tools like 'get_notes' to retrieve all notes, 'get_tags' to list all tags, and 'get_notes_like' to search for specific content.