Discover Awesome MCP Servers

mcp-test-server

A lightweight MCP test server for verifying client connectivity, providing tools, resources, and prompts for integration.

Real Estate Investment MCP Server

An MCP server that connects to a SQLite database of Zillow real estate data, enabling users to explore property values, rent indexes, and forecasts through a chat interface to make informed investment decisions.

Chrome DevTools MCP

Enables AI coding assistants to control and inspect a live Chrome browser through DevTools for automated testing, performance analysis, debugging, and web scraping. Provides reliable browser automation using Puppeteer with comprehensive DevTools access.

Final Cut Pro MCP Server

Enables comprehensive remote control and automation of Final Cut Pro through 99 tools covering timeline editing, project management, and AI-powered features. It facilitates complex workflows including media organization, color grading, and FCPXML generation using AppleScript and JXA automation.

MCP Starter for Puch AI

A starter template for creating MCP servers that work with Puch AI, featuring ready-to-use tools for job searching and image processing. Includes examples for Bearer token authentication, OAuth integration with Google and GitHub, and demonstrates user-scoped data management.

MIRO Whiteboard Connector

一个模型上下文协议服务器，用于连接到 MIRO 白板应用程序。 允许白板操作、便签创建、批量操作等。

Kubernetes MCP Server

A Model Control Protocol server that extends AI assistants with Kubernetes operations capabilities, allowing for managing deployments, pods, services and other K8s resources.

Dropbox Integration Server

通过模型上下文协议启用与 Dropbox 的交互，提供文件管理、上传、下载、删除和令牌更新等工具，并具有安全的运行时身份验证。

Mcp Assignment

测试你的 Minecraft 服务器。 (Cèshì nǐ de Minecraft fúwùqì.)

Satori Syntax MCP Server

Enables generation of Satori syntax templates for creating engaging 140-character X (Twitter) posts. Supports five different structure types including basic forms, contrarian takes, news-based content, shocking news, and step-by-step guides.

Medium MCP Server

Enables AI assistants to interact with Medium's platform for publishing, updating, and managing articles and drafts through OAuth 2.0 authentication with automatic retry logic and rate limit handling.

SAP Documentation MCP Server

Provides offline access to SAP documentation and real-time SAP Community content, integrating official documentation with community-driven solutions for comprehensive developer support.

MCP Joke Server with Authentication

好的，我会尽力理解并翻译您的要求。 您的意思是您想尝试使用 `mcp-servers`，并特别关注 `mcp-client` 的身份验证选项，对吗？ 翻译成中文是： **尝试使用 mcp-servers，并探索 mcp-client 的身份验证选项。** 更详细一点，可以翻译成： **玩转 mcp-servers，并深入研究 mcp-client 的各种身份验证方式。** 或者，如果想表达更强的动手实践的意味，可以翻译成： **动手实践 mcp-servers，重点研究 mcp-client 的身份验证选项。** 总而言之，根据您想表达的侧重点，可以选择以上任何一种翻译。 它们都表达了您想探索 `mcp-servers` 和 `mcp-client` 身份验证选项的意图。 希望这个翻译对您有帮助！ 如果您有其他问题或需要更具体的翻译，请随时告诉我。

MCP Argentina Datos

A Model Context Protocol server that provides tools to access information about Argentina through the Argentina Datos API, including holidays, presidential events, dollar exchange rates, and legislative data.

MCP Server Bootcamp

A comprehensive free bootcamp that teaches the creation of Model Context Protocol (MCP) servers, covering everything from basics to advanced enterprise architectures in 7 weeks.

tui-mcp

What Chrome DevTools MCP is for the browser, tui-mcp is for the terminal. Launch any TUI app, take screenshots, send keystrokes, read text - works with any framework.

Subgraph Registry MCP

Agent-friendly semantic classification of all subgraphs on The Graph Network. Pre-computed index of 15,500+ subgraphs with domain classification, protocol type detection, schema fingerprinting, canonical entity mapping, and composite reliability scoring.

Cloudflare Playwright MCP

Enables AI assistants to control a browser through Playwright on Cloudflare Workers, allowing them to perform web automation tasks like navigation, typing, clicking, and taking screenshots.

Minecraft Survival MCP Server

Enables LLM agents to play and survive in Minecraft by abstracting low-level tasks like pathfinding, building, and crafting into high-level transactional commands. It utilizes a "Helix" architecture to handle execution and coordinate math autonomously, allowing models to focus on strategy and high-level intent.

MCP Todo.txt Integration

A server implementation that enables LLMs to programmatically manage tasks in Todo.txt files using the Model Context Protocol (MCP), supporting operations like adding, completing, deleting, listing, searching, and filtering tasks.

Dental Clinic Loan Verification MCP Server

Enables automated dental clinic loan verification by combining rule-based ID validation with LLM-powered document analysis and fraud detection. It supports provider-agnostic vision and reasoning tools to assess document consistency, verify credentials like PAN and GST, and generate comprehensive risk narratives.

Plane MCP Server

A Model Context Protocol (MCP) server that enables LLMs to interact with Plane.so, allowing them to manage projects and issues through Plane's API. Using this server, LLMs like Claude can directly interact with your project management workflows while maintaining user control and security.

MCP

Okay, here's a breakdown of how you might configure an MCP (presumably a "Management Console Platform" or similar) server to view company information and stock prices using Claude (likely referring to Anthropic's Claude AI model). This is a conceptual outline, as the specific steps will depend heavily on the MCP software you're using. **I. Understanding the Components** * **MCP Server:** This is the central system that manages and displays information. It likely has a database, a user interface, and some form of scripting or configuration capabilities. * **Claude AI:** This is the AI model that will provide the company information and stock price data. You'll need to interact with it through its API. * **Data Sources:** Claude will need access to reliable data sources for company information and stock prices. This might include: * **Financial APIs:** APIs like Alpha Vantage, IEX Cloud, or Finnhub provide real-time and historical stock data. * **Company Information Databases:** APIs or databases like Crunchbase, Clearbit, or even Wikipedia can provide company descriptions, industry information, and key personnel. **II. High-Level Steps** 1. **Choose and Set Up Data Sources:** * **Select APIs:** Research and choose the financial and company information APIs that best suit your needs (consider cost, data coverage, and ease of use). * **API Keys:** Obtain API keys from the chosen providers. Store these securely (e.g., using environment variables or a secrets management system). 2. **Develop an API Integration Layer (Middleware):** * **Purpose:** This layer acts as an intermediary between your MCP server and the Claude API and data sources. It handles: * **API Calls:** Making requests to the financial and company information APIs. * **Data Formatting:** Transforming the data from the APIs into a format that Claude can understand. * **Error Handling:** Managing API errors and retries. * **Rate Limiting:** Respecting the API rate limits to avoid being blocked. * **Technology:** You can build this layer using languages like Python, Node.js, or Java. Python is often a good choice due to its rich ecosystem of libraries for data science and API interaction. 3. **Integrate with Claude AI:** * **Claude API Access:** Obtain access to the Claude API (you'll likely need to sign up for an account with Anthropic). * **Prompt Engineering:** Craft effective prompts for Claude to extract the desired information. For example: * "Summarize the key financial information for [Company Name] based on the following data: [Financial Data]." * "Provide a brief overview of [Company Name], including its industry, key products, and recent news." * "What is the current stock price of [Stock Ticker]?" * **API Calls to Claude:** Send the formatted data and prompts to the Claude API. * **Response Handling:** Parse the response from Claude and extract the relevant information. 4. **Configure the MCP Server:** * **Data Display:** Design the user interface within your MCP to display the company information and stock prices. * **Data Retrieval:** Configure the MCP to call your API integration layer to retrieve the data. This might involve: * **Scripting:** Using the MCP's scripting language (if it has one) to make HTTP requests to your API. * **Plugins/Extensions:** Developing a plugin or extension for the MCP that handles the data retrieval and display. * **User Interface:** Create a user-friendly interface where users can search for companies and view their information. 5. **Testing and Refinement:** * **Thorough Testing:** Test the entire system with a variety of companies and stock tickers to ensure accuracy and reliability. * **Prompt Optimization:** Refine your prompts to Claude to improve the quality of the responses. * **Error Handling:** Implement robust error handling to gracefully handle API failures and other issues. * **Performance Tuning:** Optimize the performance of the system to ensure that data is retrieved and displayed quickly. **III. Example Implementation (Conceptual - Python with Flask)** This is a simplified example to illustrate the concepts. You'll need to adapt it to your specific MCP and data sources. ```python # Python (Flask) API Integration Layer from flask import Flask, request, jsonify import requests import os app = Flask(__name__) # API Keys (replace with your actual keys) ALPHAVANTAGE_API_KEY = os.environ.get("ALPHAVANTAGE_API_KEY") CLAUDE_API_KEY = os.environ.get("CLAUDE_API_KEY") # Function to get stock price from Alpha Vantage def get_stock_price(ticker): url = f"https://www.alphavantage.co/query?function=GLOBAL_QUOTE&symbol={ticker}&apikey={ALPHAVANTAGE_API_KEY}" try: response = requests.get(url) response.raise_for_status() # Raise HTTPError for bad responses (4xx or 5xx) data = response.json() price = data['Global Quote']['05. price'] return price except requests.exceptions.RequestException as e: print(f"Error fetching stock price: {e}") return None except KeyError: print("Error: Could not parse stock price data.") return None # Function to get company information from Claude (using a placeholder) def get_company_info(company_name): # In a real implementation, you'd fetch data from a company information API # and then use Claude to summarize it. This is a simplified example. prompt = f"Provide a brief overview of {company_name}." # Replace with actual Claude API call # response = requests.post("CLAUDE_API_ENDPOINT", headers={"Authorization": f"Bearer {CLAUDE_API_KEY}"}, json={"prompt": prompt}) # company_info = response.json()["text"] company_info = f"This is placeholder information for {company_name}." return company_info @app.route("/company_data") def get_company_data(): company_name = request.args.get("company") ticker = request.args.get("ticker") if not company_name or not ticker: return jsonify({"error": "Company name and ticker are required."}), 400 stock_price = get_stock_price(ticker) company_info = get_company_info(company_name) if stock_price is None: return jsonify({"error": "Could not retrieve stock price."}), 500 data = { "company_name": company_name, "ticker": ticker, "stock_price": stock_price, "company_info": company_info, } return jsonify(data) if __name__ == "__main__": app.run(debug=True) ``` **Explanation of the Python Example:** * **Flask:** A lightweight web framework for creating the API. * **API Keys:** The code retrieves API keys from environment variables (a secure way to store them). **Important:** Never hardcode API keys directly into your code. * **`get_stock_price()`:** Fetches the stock price from the Alpha Vantage API. It includes error handling for API requests and data parsing. * **`get_company_info()`:** This is a placeholder. In a real implementation, you would: 1. Fetch company data from a company information API (e.g., Crunchbase). 2. Construct a prompt for Claude that includes the company data. 3. Send the prompt to the Claude API. 4. Parse the response from Claude to extract the company overview. * **`/company_data` endpoint:** This endpoint takes the company name and ticker as query parameters. It calls the `get_stock_price()` and `get_company_info()` functions and returns the data as a JSON response. * **Error Handling:** The code includes basic error handling to catch API errors and missing data. **How to Use the Example with Your MCP:** 1. **Deploy the API:** Deploy the Python Flask API to a server (e.g., using Heroku, AWS, or Google Cloud). 2. **Configure Your MCP:** In your MCP, you would need to: * Create a user interface element (e.g., a search box) where users can enter the company name and ticker. * Use the MCP's scripting language or plugin system to make an HTTP request to your API endpoint (e.g., `http://your-api-server/company_data?company=Apple&ticker=AAPL`). * Parse the JSON response from the API and display the data in the MCP's user interface. **IV. Important Considerations** * **Security:** Protect your API keys and ensure that your API is secure. Consider using authentication and authorization to control access to the API. * **Scalability:** If you expect a large number of users, you'll need to design your API to be scalable. Consider using a load balancer and caching to improve performance. * **Cost:** Be aware of the costs associated with using the Claude API and the financial and company information APIs. Monitor your usage and set limits to avoid unexpected charges. * **Data Accuracy:** The accuracy of the data depends on the quality of the data sources and the effectiveness of your prompts to Claude. Verify the data and consider using multiple data sources to improve accuracy. * **Claude API Limitations:** Be aware of Claude's context window limits and other API limitations. You may need to break down large requests into smaller chunks. * **Prompt Engineering:** Experiment with different prompts to Claude to get the best results. Consider using techniques like few-shot learning to improve the accuracy and relevance of the responses. * **Rate Limiting:** All APIs have rate limits. Implement proper rate limiting in your API integration layer to avoid being blocked. **In Summary** Integrating Claude with your MCP to view company information and stock prices involves: 1. Setting up data sources (financial and company information APIs). 2. Creating an API integration layer to handle API calls, data formatting, and error handling. 3. Integrating with the Claude API to generate summaries and insights. 4. Configuring your MCP to retrieve and display the data. 5. Thoroughly testing and refining the system. Remember to adapt this outline to the specific capabilities of your MCP server and the requirements of your application. Good luck!

MCP + DeepSeek AI Integration Server

A Node.js-based FastMCP protocol server that integrates DeepSeek AI capabilities for intelligent conversations and code analysis, providing tool invocation abilities through the MCP protocol.

Memobird MCP Server

Enables interaction with Memobird thermal printers to print text, HTML, web pages, and images directly from MCP-enabled clients. It includes tools for device binding, image conversion, and monitoring print job status.

Weather MCP Server

Enables AI assistants to access real-time US weather forecasts and alerts through the National Weather Service API.

Karakeep MCP server

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MySQL Database Access Server

一个模型上下文协议服务器，提供对 MySQL 数据库的只读访问，使大型语言模型 (LLM) 能够检查数据库模式并执行只读查询。 (Alternative, slightly more formal translation): 一个模型上下文协议服务器，用于提供对 MySQL 数据库的只读访问权限，从而允许大型语言模型 (LLM) 检查数据库结构并执行只读查询。