Discover Awesome MCP Servers

Code Execution Server

Enables execution of code in a sandbox environment with integrated web search capabilities. Provides a basic framework for running code safely, primarily designed for AI agents and research applications.

DICOM-MCP

一个模型上下文协议服务器，它允许通过一个简单的笔记存储系统来处理 DICOM 医学图像。 (Or, a slightly more formal translation:) 一个模型上下文协议服务器，该服务器允许通过简易的笔记存储系统处理 DICOM 医学图像。

Last9 Observability MCP

将实时生产环境的上下文信息——日志、指标和追踪——无缝引入到你的本地环境，从而更快地自动修复代码。

Freshservice MCP server

Freshservice MCP server

Agile Luminary MCP Server

A Model Context Protocol server that connects AI clients to the Agile Luminary project management system, allowing users to retrieve project details, work assignments, and product information within AI conversations.

hugeicons-mcp

用于 Hugeicons 集成和文档的 MCP 服务器 这是一个基于 TypeScript 的 MCP 服务器，它为将 Hugeicons 集成到各种平台提供工具和资源。它实现了一个模型上下文协议 (MCP) 服务器，该服务器可以帮助 AI 助手提供使用 Hugeicons 的准确指导。

FastMail MCP Server

Enables AI-powered email management through FastMail's JMAP API with features like smart email analysis, automated organization, inbox zero automation, and intelligent reply generation. Supports advanced email operations, contact management, calendar integration, and hierarchical email organization systems.

Gemini MCP Server

一个 MCP 服务器实现，允许通过 Claude 或其他 MCP 客户端，使用谷歌的 Gemini AI 模型（特别是 Gemini 1.5 Pro），通过模型上下文协议 (Model Context Protocol)。

Mcp Qdrant Docker

Okay, here's a breakdown of Docker configuration for a Qdrant MCP (Multi-Cluster Proxy) server, along with explanations and best practices. I'll provide a `docker-compose.yml` example and discuss the key elements. **Understanding Qdrant MCP** The Qdrant MCP acts as a gateway to multiple Qdrant clusters. It handles routing requests to the appropriate cluster based on configuration. This is useful for: * **Scaling:** Distributing your data across multiple Qdrant clusters. * **Isolation:** Separating data for different tenants or applications. * **High Availability:** Routing around failed clusters. * **Geo-Distribution:** Placing data closer to users. **`docker-compose.yml` Example** ```yaml version: "3.9" services: qdrant-mcp: image: qdrant/qdrant-mcp:latest # Or specify a version ports: - "6333:6333" # MCP API port - "6334:6334" # MCP GRPC port environment: QDRANT_MCP_CONFIG_PATH: /qdrant-mcp/config/config.yaml # Path to your config file volumes: - ./config:/qdrant-mcp/config # Mount your config directory restart: unless-stopped depends_on: - qdrant-cluster-1 # Replace with your actual cluster service names - qdrant-cluster-2 # Replace with your actual cluster service names # Add more dependencies as needed qdrant-cluster-1: image: qdrant/qdrant:latest # Or specify a version ports: - "6335:6333" # Cluster 1 API port environment: QDRANT__SERVICE__GRPC_PORT: 6336 volumes: - qdrant_data_1:/qdrant/storage restart: unless-stopped qdrant-cluster-2: image: qdrant/qdrant:latest # Or specify a version ports: - "6337:6333" # Cluster 2 API port environment: QDRANT__SERVICE__GRPC_PORT: 6338 volumes: - qdrant_data_2:/qdrant/storage restart: unless-stopped volumes: qdrant_data_1: qdrant_data_2: ``` **Explanation:** 1. **`version: "3.9"`:** Specifies the Docker Compose file version. Use a version compatible with your Docker installation. 2. **`services:`:** Defines the services (containers) that will be run. 3. **`qdrant-mcp:`:** The service for the Qdrant MCP. * **`image: qdrant/qdrant-mcp:latest`:** Uses the official Qdrant MCP Docker image. **Important:** Consider using a specific version tag (e.g., `qdrant/qdrant-mcp:v1.5.0`) instead of `latest` for production to ensure consistent behavior. * **`ports:`:** Maps the container ports to the host ports. * `6333:6333`: The main Qdrant MCP API port (HTTP). You'll use this to send requests to the MCP. * `6334:6334`: The Qdrant MCP gRPC port. * **`environment:`:** Sets environment variables for the container. * `QDRANT_MCP_CONFIG_PATH: /qdrant-mcp/config/config.yaml`: Specifies the path to the MCP configuration file *inside* the container. This is crucial. * **`volumes:`:** Mounts a directory from your host machine into the container. * `./config:/qdrant-mcp/config`: Mounts the `./config` directory on your host to `/qdrant-mcp/config` inside the container. This is where you'll place your `config.yaml` file. **You MUST create this `./config` directory and put your `config.yaml` file in it.** * **`restart: unless-stopped`:** Automatically restarts the container if it crashes, unless you explicitly stop it. Good for reliability. * **`depends_on:`:** Specifies dependencies. The MCP will only start *after* the listed services (your Qdrant clusters) are running. **Important:** Replace `qdrant-cluster-1` and `qdrant-cluster-2` with the actual names of your Qdrant cluster services in your `docker-compose.yml`. Add more as needed. 4. **`qdrant-cluster-1` and `qdrant-cluster-2`:** Example Qdrant cluster services. You'll need to configure these according to your needs. * **`image: qdrant/qdrant:latest`:** Uses the official Qdrant Docker image. Again, use a specific version tag for production. * **`ports:`:** Maps the container ports to the host ports. Make sure these ports don't conflict with each other or with the MCP. * **`environment:`:** Sets environment variables for the container. The `QDRANT__SERVICE__GRPC_PORT` is important for internal communication within the cluster. * **`volumes:`:** Mounts a volume for persistent storage of the Qdrant data. `qdrant_data_1:/qdrant/storage` creates a named volume. * **`restart: unless-stopped`:** Automatically restarts the container if it crashes. 5. **`volumes:`:** Defines named volumes for persistent storage. This is important so your data isn't lost when the containers are stopped or restarted. **`config.yaml` (Qdrant MCP Configuration)** This is the most important part. The `config.yaml` file tells the MCP how to route requests to your Qdrant clusters. Here's an example: ```yaml clusters: cluster1: address: "qdrant-cluster-1:6333" # Use the service name and port cluster2: address: "qdrant-cluster-2:6333" # Use the service name and port collection_mappings: my_collection: cluster: cluster1 # All requests for "my_collection" go to cluster1 another_collection: cluster: cluster2 # All requests for "another_collection" go to cluster2 shared_collection: cluster: cluster1 # All requests for "shared_collection" go to cluster1 ``` **Explanation of `config.yaml`:** * **`clusters:`:** Defines the Qdrant clusters that the MCP will route to. * `cluster1`, `cluster2`: Arbitrary names for your clusters. Use descriptive names. * `address`: The address of the Qdrant cluster. **Crucially, use the Docker service name (e.g., `qdrant-cluster-1`) and the internal port (6333 by default).** Docker's internal DNS will resolve the service name to the container's IP address. Do *not* use `localhost` or the host's IP address here. * **`collection_mappings:`:** Defines how collections are mapped to clusters. * `my_collection`, `another_collection`, `shared_collection`: The names of your Qdrant collections. * `cluster`: The name of the cluster (as defined in the `clusters` section) that should handle requests for this collection. **Important Considerations and Best Practices:** * **Version Pinning:** Always use specific version tags for your Docker images (e.g., `qdrant/qdrant-mcp:v1.5.0`, `qdrant/qdrant:v1.5.0`) instead of `latest` in production. This prevents unexpected behavior when the images are updated. * **Configuration Management:** Use a proper configuration management system (e.g., environment variables, configuration files) to manage your Qdrant and MCP settings. Avoid hardcoding values in your Dockerfiles or Compose files. * **Networking:** Docker Compose automatically creates a default network for your services. This allows the services to communicate with each other using their service names. If you need more complex networking, you can define custom networks. * **Health Checks:** Implement health checks for your Qdrant clusters and the MCP. This allows Docker to automatically restart unhealthy containers. See the Qdrant documentation for details on health check endpoints. * **Logging:** Configure logging for your Qdrant clusters and the MCP. This is essential for troubleshooting. Docker can collect logs from the containers and send them to a central logging system. * **Monitoring:** Monitor the performance of your Qdrant clusters and the MCP. Use metrics to track CPU usage, memory usage, disk I/O, and network traffic. * **Security:** Secure your Qdrant clusters and the MCP. Use authentication and authorization to control access to your data. Consider using TLS/SSL to encrypt communication between the MCP and the clusters. * **Resource Limits:** Set resource limits (CPU, memory) for your containers to prevent them from consuming too many resources. * **Backup and Restore:** Implement a backup and restore strategy for your Qdrant data. * **Testing:** Thoroughly test your Qdrant MCP setup before deploying it to production. * **Qdrant Documentation:** Refer to the official Qdrant documentation for the most up-to-date information and best practices: [https://qdrant.tech/documentation/](https://qdrant.tech/documentation/) **How to Run:** 1. **Create the `config` directory:** `mkdir config` 2. **Create the `config.yaml` file:** Place the `config.yaml` file (with your cluster definitions and collection mappings) in the `config` directory. 3. **Save the `docker-compose.yml` file:** Save the `docker-compose.yml` file in the same directory as the `config` directory. 4. **Run Docker Compose:** `docker-compose up -d` (This will start the containers in detached mode.) **Troubleshooting:** * **Check the logs:** Use `docker-compose logs qdrant-mcp` (or the name of your MCP service) to view the logs for the MCP container. Look for errors related to configuration, cluster connections, or routing. * **Verify the configuration:** Double-check the `config.yaml` file for errors. Make sure the cluster addresses are correct and that the collection mappings are accurate. * **Check network connectivity:** Make sure the MCP container can communicate with the Qdrant cluster containers. You can use `docker exec -it qdrant-mcp bash` to enter the MCP container and then use tools like `ping` or `telnet` to test connectivity. * **Qdrant Cluster Status:** Ensure your Qdrant clusters are running and healthy *before* starting the MCP. **Chinese Translation of Key Terms:** * **Qdrant MCP (Multi-Cluster Proxy):** Qdrant 多集群代理 (Duō jíqún dàilǐ) * **Cluster:** 集群 (Jíqun) * **Collection:** 集合 (Jíhé) * **Configuration:** 配置 (Pèizhì) * **Docker Compose:** Docker Compose * **Service:** 服务 (Fúwù) * **Image:** 镜像 (Jìngxiàng) * **Container:** 容器 (Róngqì) * **Port:** 端口 (Duānkǒu) * **Environment Variable:** 环境变量 (Huánjìng biànliàng) * **Volume:** 卷 (Juǎn) * **Mapping:** 映射 (Yìngshè) This comprehensive guide should help you set up a Qdrant MCP server using Docker. Remember to adapt the configuration to your specific needs and environment. Good luck!

MCP Test

带有 GitHub 集成的 MCP 服务器 (Dài yǒu GitHub jíchéng de MCP fúwùqì)

Harvest Time Tracking MCP Server

用于 Harvest 时间追踪的 MCP (模型上下文协议) 服务器。

Focus Data SQL Server

一个基于 FocusSearch 关键词解析的 NL2SQL 插件，提供更高的准确率、更快的速度和更强的可靠性！

mcp-proxy

mcp proxy

Grabba MCP Server

Microservice Connector Protocol server that exposes Grabba API functionalities as callable tools, allowing AI agents and applications to interact with Grabba's data extraction and management services.

mcp-scraper-engine

用于网页抓取的简易 MCP 服务器 (Yòng yú wǎngyè zhuā qǔ de jiǎnyì MCP fúwùqì) Alternatively, depending on the context, you could also say: 用于网络爬虫的基础 MCP 服务器 (Yòng yú wǎngluò páchóng de jīchǔ MCP fúwùqì) **Explanation of the terms:** * **用于 (Yòng yú):** Used for / For * **网页抓取 (Wǎngyè zhuā qǔ):** Web scraping (literally "web page grabbing") * **网络爬虫 (Wǎngluò páchóng):** Web crawler / Spider (more technical term for web scraping) * **基础 (Jīchǔ):** Basic / Fundamental * **简易 (Jiǎnyì):** Simple / Easy * **MCP 服务器 (MCP fúwùqì):** MCP Server (MCP is usually kept as is, as it's an acronym) The first translation is more common and generally understood. The second is more precise if you're talking about a more technical implementation of web scraping.

mcp-searxng

关于一个用于让 AI Agent 可通过 SearXNG 服务来搜索外部网站内容与信息的 MCP 服务器。

LumiFAI MCP Technical Analysis Server

好的，这是将英文翻译成中文： Provides technical analysis tools for cryptocurrency trading data, calculating EMAs (12 and 26 periods) for Binance pairs using MongoDB for data storage. **中文翻译：** 提供加密货币交易数据的技术分析工具，使用 MongoDB 存储数据，并计算币安交易对的 EMA（12 期和 26 期）。 **更详细的翻译，可以根据上下文进行调整：** * **更侧重功能描述：** 提供加密货币交易数据的技术分析工具，该工具使用 MongoDB 存储数据，并计算币安交易对的 12 期和 26 期指数移动平均线 (EMA)。 * **更侧重技术实现：** 构建用于加密货币交易数据的技术分析工具，该工具利用 MongoDB 存储数据，并计算币安交易对的 12 期和 26 期 EMA。 选择哪个翻译版本取决于你希望强调的重点。

OpenAI Image Generation MCP Server

Provides tools for generating and editing images using OpenAI's gpt-image-1 model via an MCP interface, enabling AI assistants to create and modify images based on text prompts.

GKE Hub API MCP Server

An auto-generated MCP server that enables interaction with Google Kubernetes Engine Hub API for multi-cluster management through natural language commands.

PyMCPAutoGUI

一个 MCP 服务器，它将 AI 代理与 GUI 自动化功能桥接起来，使它们能够控制鼠标、键盘、窗口并截取屏幕截图，从而与桌面应用程序进行交互。

StarRocks MCP Server

这个 MCP 服务器提供与 Starrocks 的连接，让您能够以最小的努力探索这个查询引擎。

Storyden

A modern community hub with forum and knowledge base. Native MCP built-in, ready for the next era of internet culture.

Slack MCP Server

Enables comprehensive Slack workspace integration through AI assistants, allowing users to manage channels, send messages, upload files, search conversations, and interact with users through natural language commands.

Perplexity Sonar MCP Server

用于将 Perplexity API 集成到 Claude Desktop 和其他 MCP 客户端的 MCP 服务器

MCP FishAudio Server

An MCP (Model Context Protocol) server that provides seamless integration between Fish Audio's Text-to-Speech API and LLMs like Claude, enabling natural language-driven speech synthesis.

MCP File Server

用于读取和写入本地文件的 MCP 服务器 (Yòng yú dúqǔ hé xiě rù běndì wénjiàn de MCP fúwùqì) Alternatively, depending on the specific context, you might also say: 本地文件读写 MCP 服务器 (Běndì wénjiàn dú xiě MCP fúwùqì)