发现优秀的 MCP 服务器

Web-QA

An AI-powered MCP server that automates web testing workflows by enabling recording, execution, and discovery of tests through natural language prompts.

Next.js MCP Server

A Model Context Protocol server built with Next.js that provides AI assistants with access to custom tools and resources. Includes example tools for echoing messages and performing mathematical operations, with support for both SSE and HTTP transports.

MCP

For interacting with Algolia, "MCP servers" likely refers to **Management Console Protocol (MCP) servers**. However, Algolia doesn't directly use a concept called "MCP servers" in the traditional sense. Instead, Algolia provides several ways to manage and interact with your Algolia application, including: * **Algolia Dashboard:** This is the primary web-based interface for managing your Algolia application. You can configure indexes, manage API keys, view analytics, and perform other administrative tasks. * **Algolia API Clients:** These are libraries available in various programming languages (e.g., JavaScript, Python, PHP, Java, Ruby, Go, Swift, Kotlin) that allow you to programmatically interact with the Algolia API. These clients handle the communication with Algolia's servers. * **Algolia CLI (Command-Line Interface):** A command-line tool for managing your Algolia application from the terminal. * **Algolia Integrations:** Algolia integrates with various platforms and services, such as e-commerce platforms (e.g., Shopify, Magento), CMS systems (e.g., WordPress), and analytics tools. **Translation to Chinese:** The most accurate translation depends on the specific context. Here are a few options: * **If you want to emphasize the general concept of servers that manage Algolia:** * 用于与 Algolia 交互的 **管理服务器** (Yòng yú yǔ Algolia jiāohù de guǎnlǐ fúwùqì) - "Management servers for interacting with Algolia" * **If you want to be more specific and mention the Algolia API:** * 用于与 Algolia 交互的 **API 服务器** (Yòng yú yǔ Algolia jiāohù de API fúwùqì) - "API servers for interacting with Algolia" (This is more accurate as the API clients interact with Algolia's API servers) * **If you want to mention the Algolia Dashboard (which is a web-based interface):** * 用于与 Algolia 交互的 **管理控制台服务器** (Yòng yú yǔ Algolia jiāohù de guǎnlǐ kòngzhìtái fúwùqì) - "Management console servers for interacting with Algolia" (This is less common, as the dashboard is accessed through a web browser, not directly through a server connection) * **If you want to translate "MCP servers" literally, but with a note that it's not a standard Algolia term:** * 用于与 Algolia 交互的 **MCP 服务器** (Yòng yú yǔ Algolia jiāohù de MCP fúwùqì) - "MCP servers for interacting with Algolia" (Note: Algolia 本身不使用 "MCP 服务器" 这个术语 (Note: Algolia běnshēn bù shǐyòng "MCP fúwùqì" zhège shùyǔ) - Note: Algolia itself does not use the term "MCP servers") **Recommendation:** The best translation is likely **用于与 Algolia 交互的 API 服务器 (Yòng yú yǔ Algolia jiāohù de API fúwùqì)** because the Algolia API is the primary way to programmatically interact with Algolia's services. If you're referring to the web interface, then **用于与 Algolia 交互的 管理控制台服务器 (Yòng yú yǔ Algolia jiāohù de guǎnlǐ kòngzhìtái fúwùqì)** would be more appropriate, but less common. Avoid using "MCP servers" directly unless you're sure that's the intended terminology, and even then, include a clarifying note.

Watchtower DAP Windows Debugging

Enables step-through debugging for C#, Node.js/TypeScript, Python, and Dart applications on Windows through a unified MCP interface. Acts as a bridge between MCP clients and various debug adapters, providing consistent debugging workflows with breakpoints, variable inspection, and process attachment capabilities.

ServiceNow MCP Server

A Model Context Protocol server that enables AI assistants and development tools to interact with ServiceNow instances, providing comprehensive API coverage for incident management, change management, CMDB, and other ServiceNow modules.

Feedback Collector MCP

Collects user feedback with text and image support through an Electron app, allowing AI tools to gather and process user input with customizable prompts and multiple response options.

Autodesk Platform Services MCP Server

Autodesk Platform Services MCP 服务器 (Autodesk Platform Services MCP fúwùqì)

Aidderall MCP Server

Provides AI assistants with a hierarchical task management system that maintains focus and context across complex problem-solving sessions, solving context window limitations through organized task structures.

AWS Nova Canvas MCP Server

一个 MCP 服务器，允许您使用 Amazon Bedrock 的 Nova Canvas 模型来生成和编辑图像，支持诸如文本到图像生成、图像修复（inpainting）、图像外延（outpainting）、图像变体和背景移除等功能。

MCP-RQuest

一个模型上下文协议服务器，使 Claude 和其他大型语言模型能够发起带有逼真浏览器指纹的 HTTP 请求，绕过常见的反爬虫措施，并以更自然的方式与网站交互。

Claude Desktop Transport Bridge

一个 Stdio MCP 服务器，提供连接到使用其他传输协议的服务器的桥梁。

Tiny Chat

这是一个具有聊天功能的LLM应用程序，它具有使用RAG的聊天功能、数据库和MCP服务器功能。UI专为日本用户设计。

PostgreSQL MCP Server

Provides access to PostgreSQL database schemas and metadata, allowing MCP-compatible tools like Cursor to explore database structure, inspect table schemas, and understand relationships.

🧠 Model Context Protocol (MCP)

好的，这是使用 Langchain MCP Adapters 和 Ollama 实现 MCP 的演示： **标题：使用 Langchain MCP Adapters 和 Ollama 实现 MCP 的演示** **简介：** 本演示展示了如何使用 Langchain MCP Adapters 和 Ollama 来实现 MCP（多通道处理）。MCP 是一种技术，它允许您使用多个通道（例如，文本、图像、音频）来处理数据。这可以提高准确性和效率。 **先决条件：** * 已安装 Python 3.7 或更高版本 * 已安装 Langchain * 已安装 Ollama * 已安装 Langchain MCP Adapters **安装：** ```bash pip install langchain pip install ollama pip install langchain-mcp-adapters ``` **代码：** ```python from langchain_mcp_adapters import MultiChannelProcessor from langchain.llms import Ollama from langchain.chains import LLMChain from langchain.prompts import PromptTemplate # 1. 定义你的通道。 # 在这个例子中，我们将使用两个通道：文本和图像。 channels = [ { "name": "text", "type": "text", }, { "name": "image", "type": "image", }, ] # 2. 创建一个多通道处理器。 mcp = MultiChannelProcessor(channels=channels) # 3. 定义你的提示模板。 # 这个提示模板将用于处理文本通道。 text_prompt_template = """ 你是一个有用的助手。 请回答以下问题： {question} """ text_prompt = PromptTemplate( input_variables=["question"], template=text_prompt_template, ) # 4. 定义你的语言模型。 # 在这个例子中，我们将使用 Ollama。 llm = Ollama(model="llama2") # 5. 创建一个 LLM 链。 text_chain = LLMChain(llm=llm, prompt=text_prompt) # 6. 将 LLM 链添加到多通道处理器。 mcp.add_channel("text", text_chain) # 7. 定义一个函数来处理图像通道。 def image_processor(image_path): """ 这个函数将处理图像通道。 Args: image_path: 图像的路径。 Returns: 图像的描述。 """ # 在这里，你可以使用任何图像处理库来处理图像。 # 在这个例子中，我们将使用 PIL 库。 from PIL import Image import pytesseract # 打开图像。 image = Image.open(image_path) # 使用 pytesseract 来提取图像中的文本。 text = pytesseract.image_to_string(image) # 返回图像的描述。 return text # 8. 将图像处理器添加到多通道处理器。 mcp.add_channel("image", image_processor) # 9. 创建一个输入。 input_data = { "text": { "question": "什么是 Langchain？", }, "image": { "image_path": "image.png", }, } # 10. 处理输入。 output = mcp.process(input_data) # 11. 打印输出。 print(output) ``` **解释：** 1. **定义通道：** 首先，我们定义了两个通道：文本和图像。每个通道都有一个名称和一个类型。 2. **创建多通道处理器：** 接下来，我们创建了一个多通道处理器。多通道处理器负责处理来自不同通道的数据。 3. **定义提示模板：** 我们定义了一个提示模板，用于处理文本通道。提示模板是一个字符串，它包含一个或多个占位符。占位符将被输入数据替换。 4. **定义语言模型：** 我们定义了一个语言模型。语言模型是一个可以生成文本的模型。在这个例子中，我们使用 Ollama。 5. **创建 LLM 链：** 我们创建了一个 LLM 链。LLM 链是一个将提示模板和语言模型连接在一起的链。 6. **将 LLM 链添加到多通道处理器：** 我们将 LLM 链添加到多通道处理器。这告诉多通道处理器使用 LLM 链来处理文本通道。 7. **定义图像处理器：** 我们定义了一个图像处理器。图像处理器是一个可以处理图像的函数。 8. **将图像处理器添加到多通道处理器：** 我们将图像处理器添加到多通道处理器。这告诉多通道处理器使用图像处理器来处理图像通道。 9. **创建输入：** 我们创建了一个输入。输入是一个字典，它包含每个通道的数据。 10. **处理输入：** 我们处理输入。多通道处理器将使用 LLM 链和图像处理器来处理输入数据。 11. **打印输出：** 我们打印输出。输出是一个字典，它包含每个通道的处理结果。 **结论：** 本演示展示了如何使用 Langchain MCP Adapters 和 Ollama 来实现 MCP。MCP 是一种强大的技术，它可以提高准确性和效率。 **注意：** * 您需要将 `image.png` 替换为实际的图像文件。 * 您需要根据您的需要修改提示模板和图像处理器。 * 您可以使用任何语言模型来代替 Ollama。 希望这个演示对您有所帮助！

Dify MCP Server

集成了 Dify AI API，为 Ant Design 组件提供代码生成功能，支持文本和图像输入，并具备流式处理能力。

WordPressMCP Server

Enables interaction with WordPress sites through the REST API, supporting content management for posts, pages, users, plugins, and custom post types with Application Password authentication.

RTIdeas MCP API Server

Converts a local MCP server into a remote HTTP-accessible REST API server with MongoDB support for managing brainstorming sessions and ideas. Provides endpoints for listing sessions, searching ideas, analyzing connections, and generating statistics.

Vercel MCP Adapter

Enables real-time communication between applications and AI models using the Model Context Protocol, supporting features like custom tools and multiple transport options for Next.js applications.

ghas-mcp-server

镜子 (jìng zi)

System Designer MCP Server

Enables AI agents to create, validate, and export UML system models using structured MSON format. Supports generating PlantUML and Mermaid diagrams with direct export to System Designer macOS application.

Jina AI MCP Tools

一个与 Jina AI Search Foundation API 集成的模型上下文协议 (MCP) 服务器。

MCP Jibun Server

Enables AI agents to read and retrieve the latest posts from Jibun and Ech0 instances. It allows users to list configured sources and fetch content with support for pagination and source selection.

Weather MCP Tool

A Model Context Protocol tool that provides weather information for cities, with London access requiring Solana devnet payment via the Latinum Wallet MCP server.

Browser Automation MCP Server

一个模型上下文协议（MCP）服务器，为 Claude 和其他 MCP 兼容的 AI 助手提供浏览器自动化功能。

MCP Appium

Enables AI assistants to automate mobile app testing and development for iOS and Android through natural language interactions. Supports intelligent element identification, session management, automated test generation, and comprehensive device interactions including clicks, swipes, screenshots, and app management.

Quickbase MCP Server

Provides a standardized interface for interacting with Quickbase's JSON RESTful API through Claude and other MCP clients, supporting operations like querying records, managing table relationships, and handling file attachments.

MCP Servers

一个 Node.js 和 TypeScript 服务器项目，提供了一个简单的入门示例，使用 Express.js Web 服务器，并支持热重载、测试和模块化结构。

Health API MCP Server

Enables interaction with a comprehensive healthcare management system through FastAPI, supporting operations for patients, doctors, appointments, medical records, telemedicine, lab orders, prescriptions, insurance claims, and more with JWT authentication.