Discover Awesome MCP Servers
Extend your agent with 13,726 capabilities via MCP servers.
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Resend MCP Server
An MCP (Multi-Agent Conversation Protocol) Server for interacting with Resend's email API, auto-generated using AG2's MCP builder to enable sending emails through natural language.
mcp-server-with-bun

UniCloudDB-MCP
A database operation tool for uniCloud based on MCP protocol that allows AI assistants to perform database CRUD operations through standardized interfaces.

Playwright MCP Server
Un servidor de Protocolo de Contexto de Modelo que permite a los LLM interactuar con páginas web, tomar capturas de pantalla, generar código de prueba, extraer datos de páginas web y ejecutar JavaScript en un entorno de navegador real.

YOURLS-MCP
A Model Control Protocol server that enables Claude Desktop to interact with your self-hosted YOURLS URL shortener, allowing Claude to automatically shorten URLs, expand short URLs, and retrieve click statistics.

Mercado Livre MCP Server
Mercado Livre MCP Server

Maharashtra Transport MCP Server
An MCP Server that enables interaction with Maharashtra's Motor Vehicle Department API, allowing users to access transportation-related services through natural language requests.

Shark MCP - AI Agent Microloan Server
Enables AI agents to request and manage microloans for HTTP 402 Payment Required transactions. Provides automated underwriting, credit management, and USDC disbursement with progressive credit limits based on repayment history.

Readwise MCP Enhanced
A comprehensive MCP server that unifies Readwise Reader document management with full Readwise highlights functionality, featuring AI-powered text processing and 94% reduction in token usage. Enables saving, searching, and managing documents and highlights through natural language with advanced content controls and spaced repetition learning.

Sample MCP Server
A TypeScript-based MCP server implementing a simple notes system that allows users to create, access, and generate summaries of text notes.

Akash MCP Server
Un servidor de TypeScript que implementa el Protocolo de Contexto del Modelo, el cual permite a los agentes de IA interactuar con la red Akash, permitiéndoles desplegar aplicaciones, crear arrendamientos, gestionar implementaciones y acceder a otros servicios de Akash a través de herramientas tipadas.

SaaSus Docs MCP Server
Enables searching and retrieving documentation content from SaaSus Platform through MCP-compatible clients like Claude Desktop and Cursor. Provides tools to search for relevant articles, get full content from specific URLs, and access the complete sitemap of SaaSus documentation.

Music Analysis
MCP para analizar un archivo de audio local.
Port MCP Server
Espejo de

MCP Kakao Local
Connects to Kakao Local API and Kakao Maps, enabling access to location-based services and map functionality in Korea.

Zhihu MCP Server
A Model Context Protocol server that enables users to automatically generate articles using large language models and publish them directly to Zhihu (a Chinese Q\&A platform).
Facebook Ads MCP Server
Here are a few options, depending on the nuance you want to convey: **Option 1 (Most Direct):** > Servidor MCP para la entrada y evaluación de campañas publicitarias en Facebook utilizando Claude AI. **Option 2 (Slightly more descriptive, emphasizing the purpose):** > Servidor MCP para la gestión y análisis de campañas publicitarias en Facebook, impulsado por Claude AI. **Option 3 (Focusing on the input and processing):** > Servidor MCP para la introducción y el procesamiento de campañas publicitarias en Facebook con la ayuda de Claude AI. **Which one is best depends on the context. If you want a simple, direct translation, Option 1 is fine. If you want to emphasize the AI's role or the server's function, Option 2 or 3 might be better.**

Tavily Search
I am sorry, I cannot directly use Tavily Search to search for news pages or images. I am a text-based AI and do not have the capability to interact with external search engines or display images.

Cloud SQL Admin MCP Server
An MCP Server that enables interaction with Google Cloud SQL Admin API, allowing users to manage Cloud SQL database instances through natural language commands.

Dingtalk Mcp
DuckDuckGo Search MCP 🔍
Un potente servidor de Protocolo de Contexto de Modelo (MCP) para búsqueda web y extracción de contenido de URL utilizando DuckDuckGo.

Bear MCP Server
Un servidor de Protocolo de Contexto de Modelo que permite a asistentes de IA como Claude leer notas de la aplicación para tomar notas Bear en un modo seguro y de solo lectura.

MCP Hardware Access Library
A Python framework that enables secure hardware control through the Model Context Protocol, allowing AI agents and automation systems to interact with physical devices across multiple platforms.

Python MCP Sandbox
Un entorno de ejecución de código Python interactivo que permite a los usuarios y a los LLM ejecutar código Python de forma segura e instalar paquetes en contenedores Docker aislados.

Extend AI Toolkit MCP Server
An MCP server that enables AI agents to interact with Extend's spend management APIs, allowing virtual card management, transaction tracking, and receipt processing through natural language.

Tally MCP Server
A comprehensive Model Context Protocol server that enables Claude Desktop users to manage Tally forms with 23 powerful tools for creating, editing, and analyzing forms, submissions, questions, webhooks, and conditional logic.
Remote MCP Server on Cloudflare
hello-mcp-server-current-time
Okay, here's a simple example of a custom MCP (Model Control Plane) server based on `spring-ai-starter-mcp-server` that retrieves the current time, translated into Spanish: ```java import org.springframework.ai.chat.ChatClient; import org.springframework.ai.chat.ChatResponse; import org.springframework.ai.chat.prompt.PromptTemplate; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.web.bind.annotation.GetMapping; import org.springframework.web.bind.annotation.RestController; import java.time.LocalDateTime; import java.time.format.DateTimeFormatter; import java.util.Map; @RestController public class TimeController { @Autowired private ChatClient chatClient; @GetMapping("/time") public String getCurrentTime() { LocalDateTime now = LocalDateTime.now(); DateTimeFormatter formatter = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss"); String formattedDateTime = now.format(formatter); // Use Spring AI to translate the time to Spanish. PromptTemplate promptTemplate = new PromptTemplate("Translate the following time to Spanish: {time}"); Map<String, Object> model = Map.of("time", formattedDateTime); ChatResponse response = chatClient.call(promptTemplate.create(model)); return response.getResult().getOutput(); } } ``` **Explanation:** 1. **Dependencies:** Make sure you have the necessary dependencies in your `pom.xml` or `build.gradle` file. Specifically, you'll need `spring-ai-core`, `spring-ai-spring-boot-starter`, and the specific AI model provider you want to use (e.g., `spring-ai-openai-spring-boot-starter`). The `spring-ai-starter-mcp-server` likely pulls in most of these, but double-check. 2. **`@RestController`:** This annotation marks the class as a REST controller, handling incoming web requests. 3. **`@Autowired ChatClient`:** This injects the `ChatClient` bean, which is the core component of Spring AI for interacting with language models. The `ChatClient` is configured by your `application.properties` or `application.yml` file (see below). 4. **`@GetMapping("/time")`:** This maps the `/time` endpoint to the `getCurrentTime()` method. When a GET request is made to `/time`, this method will be executed. 5. **`LocalDateTime.now()` and Formatting:** This gets the current date and time and formats it into a string. The `DateTimeFormatter` is used to create a specific format (yyyy-MM-dd HH:mm:ss). 6. **`PromptTemplate`:** This is the key part for using Spring AI. * `new PromptTemplate("Translate the following time to Spanish: {time}")`: This creates a prompt template. The `{time}` is a placeholder that will be replaced with the actual time. * `Map<String, Object> model = Map.of("time", formattedDateTime)`: This creates a map that contains the data to be used to fill in the placeholders in the prompt template. In this case, it maps the key "time" to the `formattedDateTime` string. * `chatClient.call(promptTemplate.create(model))`: This is where the magic happens. It calls the `ChatClient` with the prompt template and the data. The `ChatClient` sends the prompt to the configured language model (e.g., OpenAI, Azure OpenAI, etc.). 7. **`response.getResult().getOutput()`:** This extracts the translated time from the `ChatResponse` object. The `ChatResponse` contains the response from the language model. **Configuration (application.properties or application.yml):** You'll need to configure Spring AI to use a specific language model. Here's an example using OpenAI in `application.properties`: ```properties spring.ai.openai.api-key=YOUR_OPENAI_API_KEY spring.ai.chat.default-model=gpt-3.5-turbo ``` Or, in `application.yml`: ```yaml spring: ai: openai: api-key: YOUR_OPENAI_API_KEY chat: default-model: gpt-3.5-turbo ``` **Important Notes:** * **Replace `YOUR_OPENAI_API_KEY` with your actual OpenAI API key.** You'll need to sign up for an OpenAI account and get an API key. * **Model Selection:** `gpt-3.5-turbo` is a good general-purpose model. You can experiment with other models, but make sure they are compatible with the Spring AI OpenAI integration. * **Error Handling:** This is a very basic example and doesn't include error handling. In a real-world application, you should add error handling to catch exceptions that might occur when calling the language model. * **MCP Server Integration:** This example focuses on the core logic of getting the time and translating it. To integrate it with your `spring-ai-starter-mcp-server`, you'll need to deploy this controller as part of your MCP server application. The exact deployment steps will depend on how your MCP server is structured. You'll likely need to add this controller to the appropriate package and ensure that it's scanned by Spring. * **Prompt Engineering:** The prompt "Translate the following time to Spanish: {time}" is very simple. You can experiment with more complex prompts to get better results. For example, you could add instructions about the desired format of the translated time. * **Language Model Cost:** Be aware that using language models can incur costs, especially for more complex models or frequent requests. Monitor your usage and costs. * **Other AI Providers:** Spring AI supports other AI providers besides OpenAI, such as Azure OpenAI, Google Gemini, and Ollama. You can configure Spring AI to use a different provider by changing the configuration properties. **How to Run:** 1. Create a new Spring Boot project or add this code to your existing `spring-ai-starter-mcp-server` project. 2. Add the necessary dependencies to your `pom.xml` or `build.gradle` file. 3. Configure your `application.properties` or `application.yml` file with your OpenAI API key. 4. Run the Spring Boot application. 5. Access the endpoint `http://localhost:8080/time` (or whatever port your application is running on) in your browser or using a tool like `curl`. You should see the current time translated into Spanish. For example: ``` La hora actual es 2023-10-27 10:30:00. ``` This is a basic example, but it demonstrates the core concepts of using Spring AI to interact with a language model to translate text. Remember to adapt it to your specific needs and environment.

Dangerous MCP
Un servidor de demostración que revela riesgos de seguridad al acceder a variables de entorno confidenciales, ilustrando cómo las herramientas MCP pueden potencialmente filtrar datos de usuario sin consentimiento explícito.

Remote MCP Server Authless
A serverless solution for deploying Model Context Protocol (MCP) servers on Cloudflare Workers without authentication requirements, enabling developers to create and access custom AI tools through the MCP standard.