Discover Awesome MCP Servers

Claude Fleet Monitor

Enables Claude Code sessions to query fleet status, focus terminals, and manage sessions programmatically via MCP tools.

WHMCS MCP Server

Enables AI agents to administrate WHMCS installations through the External API, providing ~50 tools for clients, billing, orders, services, domains, support, and aggregators with safety features and governance.

Port MCP Server

Espejo de

mcp-cirujanos

MCP server for scheduling appointments and managing services for plastic surgery clinics. Supports calendar operations, booking, catalog search, and case studies (before/after) for procedures.

ruru-swbot-mcp

Enables control of SwitchBot devices by name, reducing the risk of AI misidentifying device IDs.

nsight-graphics-mcp

MCP server for reading, filtering, and analyzing NVIDIA Nsight Graphics captures via ngfx-replay, exposing tools for capture inspection, GPU Trace profiling, and replay analysis.

Task Orchestrator MCP Server

A sophisticated task orchestration system with role-based workflow management and Trello integration.

IRA-RESEARCHER

A powerful browser automation MCP server with 40 tools, stealth mode, ghost effects, and full DevTools access, enabling natural language control of browsers without any API keys.

Salesforce MCP Server

Enables natural language interactions with Salesforce data and metadata, supporting queries, data manipulation, custom object/field management, Apex code operations, and debug logging across multiple authentication methods.

steam-games-mcp

Enables interaction with Steam: search games, get store details, reviews, prices, discounts, news, and player profiles, libraries, and achievements via the Steam Web API.

Revenium MCP Server

Connects AI agents to Revenium for cost tracking, alerting, and usage-based billing, enabling AI assistants to manage costs, set alerts, and handle billing operations.

mcp-ToseaAI

Official MCP server for ToseaAI that enables document-to-presentation workflows including PDF parsing, outline generation, and slide rendering. It provides a stable tool surface for AI agents to create, manage, and export presentations directly within their environment.

ShipReceipt MCP Server

Provides tools to create, run, and verify deterministic delivery receipts for completion claims, enabling reviewers to check freshness and correctness of evidence.

Vibe MCP

Browser automation MCP server that enables multiple AI agents to simultaneously control a real Chrome browser using the Vibe extension, supporting local and private automation with logged-in sessions.

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.

Tempera

Enables Claude Code with persistent memory that learns from past sessions, capturing coding episodes and surfacing relevant memories to improve over time.

Chargebee MCP Server

A server that integrates with AI-powered code editors to provide immediate answers about Chargebee products and API services, offering context-aware code snippets and access to Chargebee's knowledge base.

Recall — Memory Agent for Students

Enables students to capture and recall narrated observations from labs, lectures, or fieldwork, and generate study summaries or lab report drafts.

Enterprise Secure AWS MCP Server

Enables secure tool discovery and execution on AWS Lambda with role-based access control, command injection defense, and sensitive data redaction, allowing managed CloudWatch log queries and Terraform operations through a standard MCP interface.

Keywords Everywhere MCP Server

A Model Context Protocol server that provides access to the Keywords Everywhere API, enabling AI assistants to perform SEO research including keyword analysis, domain traffic metrics, and backlink data.

afpnews-mcp-server

MCP server exposing AFP news content as tools for AI assistants, enabling article search, retrieval, and analysis via natural language.

letmediff

A review handoff tool for agent-driven coding sessions that captures worktree diffs, creates shareable review URLs, and streams reviewer feedback back to the agent.

codebase-context-mcp

Enables codebase indexing and searching with symbolic and full-text search, supporting multiple programming languages, designed to work on any architecture including ARM64.

TypeScript Analyzer MCP Server - Enterprise Edition

Analiza y corrige cualquier error tipográfico en TypeScript con un servidor MCP inteligente: rápido, extensible y compatible con React.

Maestro MCP Server

Enables interaction with the Bitcoin blockchain through the Maestro API platform. Provides tools for exploring blocks, transactions, addresses, mempool monitoring, market prices, wallet operations, and node RPC calls on Bitcoin mainnet and testnet4.

mcp-portico

MCP Portico is an MCP server that turns OpenAPI descriptions or inspected backend source code into policy-controlled MCP connections, exposing multiple backend systems with tenant isolation and credential security.

ai-video-mcp

Turns text scripts into complete videos with stock footage, AI narration, and subtitles via MCP tools for AI assistants.

Excel Chart MCP Server

A dual-mode intelligent Excel processing server that provides Excel data analysis tools for Cursor AI in MCP mode and offers a standalone web interface with support for external AI configurations like DeepSeek.

Secure Command Executor MCP Server

Un servicio robusto de ejecución de comandos con rotación diaria de registros, diseñado para gestionar y ejecutar de forma segura comandos del sistema con comprobaciones de seguridad y registro.

civ6-mcp

An MCP server that lets LLM agents play full games of Civilization VI. It connects to a running game and provides tools for unit movement, city management, diplomacy, and more, all through the game's rule-enforcing APIs.