Discover Awesome MCP Servers

Extend your agent with 53,204 capabilities via MCP servers.

All53,204
NeuronSearchLab

NeuronSearchLab

Enables MCP-compatible AI clients to access the NeuronSearchLab recommendation engine for fetching personalized recommendations, tracking user interactions, and managing catalogue items through natural language.

CrewAI Enterprise MCP Server

CrewAI Enterprise MCP Server

Enables kicking off deployed CrewAI workflows and inspecting their status and results.

DeepSeek MCP Server

DeepSeek MCP Server

一个服务器,通过集成 DeepSeek R1 的高级推理引擎来增强 Claude 的推理能力,从而解决复杂的推理任务。

mcp-task-tools

mcp-task-tools

Provides task and project management tools for AI agents, including todo list management, prioritization frameworks like Eisenhower Matrix and RICE scoring, time estimation using PERT, daily standup generation, and sprint burndown calculation.

FlowMCP Server

FlowMCP Server

Provides LocalServer and RemoteServer implementations for running MCP servers locally via stdio or remotely via HTTP/SSE, with simple and advanced deployment options.

Tableau MCP Server

Tableau MCP Server

Connects Claude Desktop to Tableau Server for natural language interactions with Tableau data, enabling data extraction, dashboard exports, and comprehensive administrative capabilities including user management, permission auditing, and usage analytics.

MCP Memory Server

MCP Memory Server

Enables AI assistants to store and retrieve long-term memories with semantic search, supporting various memory types and tags via PostgreSQL and pgvector.

md-pdf-mcp

md-pdf-mcp

使用 VS Code 的 Markdown 样式和 Python 的 ReportLab 将 Markdown 转换为带样式的 PDF,并带有一个简单的笔记存储系统。

ZigBee2MQTT MCP Server

ZigBee2MQTT MCP Server

Enables AI assistants to discover, monitor, and control ZigBee smart home devices through ZigBee2MQTT. Provides intelligent device discovery, state monitoring, and automation integration with support for remote deployment.

Flashlight

Flashlight

Enables whole-codebase code search using natural language queries by leveraging DeepSeek's 1M context window. Automatically shards large projects and utilizes prefix caching for cost-effective repeated searches.

Remote MCP Server on Cloudflare

Remote MCP Server on Cloudflare

Enables deployment of authentication-free MCP servers on Cloudflare Workers that can be accessed remotely from MCP clients like Claude Desktop or the Cloudflare AI Playground.

MCP ABAP Server

MCP ABAP Server

Enables querying ABAP programs, classes, function modules, and other objects from SAP systems with OAuth 2.0 authentication.

weather-mcp

weather-mcp

Provides real-time weather data and alerts from the National Weather Service API, including forecasts for US locations and active alerts for US states.

ManyContacts MCP Server

ManyContacts MCP Server

MCP server for ManyContacts WhatsApp Business CRM that enables AI agents to manage contacts, send messages, run campaigns, and configure auto-replies through comprehensive CRM operations.

System Resource Monitor MCP Server

System Resource Monitor MCP Server

为 Claude 提供实时系统监控功能,包括 CPU、内存、磁盘、网络、电池和网速指标。

Mealie MCP Server

Mealie MCP Server

An MCP server for managing recipes, meal plans, shopping lists, and more through a self-hosted Mealie instance.

Chunky MCP

Chunky MCP

An MCP server that manages chunking and reading of large responses, allowing tools to handle oversized data that would otherwise fail.

mcp-weather

mcp-weather

A Model Context Protocol (MCP) server that enables AI assistants and LLMs to access real-time weather data and forecasts by connecting to the OpenWeatherMap API.

Scira AI MCP Server

Scira AI MCP Server

Provides AI-powered search capabilities through three specialized tools: web search, people search, and X platform (formerly Twitter) search, all accessible via a Model Context Protocol interface.

Joomla MCP Server

Joomla MCP Server

Joomla MCP Server

MongoDB MCP Server

MongoDB MCP Server

Enables AI assistants to interact natively with MongoDB databases, including schema discovery, CRUD operations, aggregation pipelines, and index management via natural language.

Home Assistant MCP Server

Home Assistant MCP Server

Enables control and monitoring of Home Assistant smart home devices through MCP, allowing users to list entities, check device states, and call services to control lights, switches, sensors, and other connected devices.

MSSQL MCP Server

MSSQL MCP Server

A Model Context Protocol server that provides comprehensive access to Microsoft SQL Server databases, enabling Language Models to inspect schemas, execute queries, manage database objects, and perform advanced database operations.

Memory Server MCP

Memory Server MCP

Provides persistent memory storage with advanced features like tagging, content search, and expiration settings. It enables users to create directed links between stored memories to build structured relationships and knowledge graphs.

eaight

eaight

An AI-native web browser that exposes a full MCP server, letting Claude Code, Codex CLI, and Gemini CLI see and control the browser in real time.

bear-mcp

bear-mcp

Enables Claude to interact with Bear notes (via better-bear-cli) for listing, searching, creating, editing, and exporting notes through natural language.

Cloudera Machine Learning (CML) MCP Server

Cloudera Machine Learning (CML) MCP Server

Enables interaction with Cloudera Machine Learning to manage projects, files, and jobs through the Model Context Protocol. It supports tasks such as uploading files, scheduling jobs, and managing runtimes via natural language interfaces.

MCP Server Boilerplate

MCP Server Boilerplate

A starter template for building MCP servers with TypeScript support, example tools, and automated installation scripts for Claude Desktop, Cursor, and other MCP-compatible AI assistants. Provides a foundation for creating custom tools, resource providers, and prompt templates.

shopify-mcp

shopify-mcp

Okay, here's a translation of "for Shopify API interaction including product, customer, order" into Chinese, along with some nuances and options depending on the specific context: **Option 1 (Most General):** * **中文:** 用于 Shopify API 交互,包括产品、客户和订单。 * **Pinyin:** Yòng yú Shopify API jiāohù, bāokuò chǎnpǐn, kèhù hé dìngdān. * **Explanation:** This is a straightforward and common translation. It's suitable for general documentation or explanations. **Option 2 (More Emphasis on "Handling" or "Working With"):** * **中文:** 用于 Shopify API 交互,处理产品、客户和订单。 * **Pinyin:** Yòng yú Shopify API jiāohù, chǔlǐ chǎnpǐn, kèhù hé dìngdān. * **Explanation:** The word "处理 (chǔlǐ)" means "to handle," "to process," or "to deal with." This option is better if you want to emphasize the actions you're taking with the data. **Option 3 (More Technical, Emphasizing Data Manipulation):** * **中文:** 用于 Shopify API 交互,涉及产品、客户和订单的数据操作。 * **Pinyin:** Yòng yú Shopify API jiāohù, shèjí chǎnpǐn, kèhù hé dìngdān de shùjù cāozuò. * **Explanation:** This is a more technical translation. "涉及 (shèjí)" means "involving" or "relating to," and "数据操作 (shùjù cāozuò)" means "data manipulation." This is suitable for technical documentation or code comments. **Option 4 (More Specific to Development):** * **中文:** 用于 Shopify API 交互,开发产品、客户和订单相关功能。 * **Pinyin:** Yòng yú Shopify API jiāohù, kāifā chǎnpǐn, kèhù hé dìngdān xiāngguān gōngnéng. * **Explanation:** This option is suitable if you are talking about developing features related to product, customer and order. "开发 (kāifā)" means "to develop", and "相关功能 (xiāngguān gōngnéng)" means "related features". **Key Vocabulary:** * **Shopify API:** Shopify API (No translation needed, commonly used as is) * **交互 (jiāohù):** Interaction * **产品 (chǎnpǐn):** Product * **客户 (kèhù):** Customer * **订单 (dìngdān):** Order * **用于 (yòng yú):** Used for * **包括 (bāokuò):** Including * **处理 (chǔlǐ):** To handle, to process, to deal with * **涉及 (shèjí):** Involving, relating to * **数据操作 (shùjù cāozuò):** Data manipulation * **开发 (kāifā):** To develop * **相关功能 (xiāngguān gōngnéng):** Related features **Which option is best?** The best option depends on the context. If you're writing general documentation, Option 1 is a good choice. If you're describing the actions you're taking, Option 2 is better. If you're writing technical documentation, Option 3 might be more appropriate. If you are talking about development, Option 4 is a good choice. I hope this helps! Let me know if you have any other questions.

Proton Mail Bridge MCP

Proton Mail Bridge MCP

Professional Proton Mail management with 20+ tools, advanced analytics, and seamless Proton Bridge integration.