发现优秀的 MCP 服务器
通过 MCP 服务器扩展您的代理能力,拥有 16,364 个能力。
Cowsay MCP Server
Enables language models to generate fun ASCII art featuring cows and other characters saying or thinking custom messages. Provides access to various cow characters including dragons, penguins, and skeletons for creative text art generation.
claude-mcp-server
一个模型上下文协议服务器,使 Claude AI 能够与 Paybyrd 的支付处理 API 交互,从而可以创建支付链接、处理退款和检索订单信息。
Ordnance Survey MCP Server
A Python-based MCP server that provides access to Ordnance Survey APIs, allowing querying of geographic data through a standardized protocol with features like collection management, feature search, and spatial filtering.
Gold IRA Sales Analysis MCP Server
Enables AI assistants to analyze B2C Gold IRA sales call transcripts through 6 specialized prompts executed in strategic order. Provides structured analysis of conversation dynamics, psychology, objections, deal risk, and strategic qualification for retirement planning sales calls.
Supabase MCP Servers
将 LLM 连接到 Supabase 的 MCP 服务器集合
React Native Debugger MCP
一个 MCP 服务器,用于连接到你的 React Native 应用程序调试器。 (Yī gè MCP fúwùqì, yòng yú liánjiē dào nǐ de React Native yìngyòng chéngxù tiáoshì qì.)
Vercel MCP Server Template
A template for deploying MCP servers on Vercel with serverless functions. Includes example tools for rolling dice and getting weather data to demonstrate basic functionality and API integration patterns.
Metabase Server MCP
使 AI 助手能够与 Metabase 交互,从而通过自然语言访问仪表板、问题、数据库和用于执行查询及查看数据的工具。
AndroidTVMCP
A Model Context Protocol server that enables AI assistants to control Android TV devices, providing remote control functionality like navigation, playback control, app management, and device status monitoring.
Bear Notes MCP Server
A Model Context Protocol server that provides Claude with access to search, retrieve, and analyze notes from the Bear App through natural language queries.
NextChat-MCP-Awesome
NextChat MCP 服务器合集
Pulse CN MCP Server
一个模型上下文协议服务器,为人工智能模型提供来自中国18个主要互联网平台的实时热门内容,包括微博、知乎和哔哩哔哩。
HIPAA Guardian MCP Server
Provides comprehensive HIPAA compliance guidance for developers building healthcare applications. Offers tools to identify PHI, understand encryption requirements, navigate business associate rules, and ensure compliance with HIPAA Security and Privacy Rules.
Databutton App MCP
一个代理服务器,允许 LLM 客户端通过 MCP 协议和 Websocket 使用 Databutton 应用程序 API 端点作为工具。
🪄 ImageSorcery MCP
🪄 ImageSorcery MCP
MCP Prompts Server
通过简化的SOLID架构,实现提示词的创建、管理和模板化,允许用户按类别组织提示词,并在运行时填充模板。
keyphrases-mcp
Enables AI-driven workflows to extract keyphrases more accurately and with higher relevance using the BERT machine learning model. It works directly with your local files in the allowed directories saving the context tokens for your agentic LLM.
Shogi MCP Server
Enables AI agents to analyze shogi (Japanese chess) positions and moves by integrating with USI protocol engines. Provides position analysis, move evaluation, and game state assessment through HTTP API bridge and MCP tools.
Memory Custom
一个定制的 MCP 内存服务器,能够创建和管理知识图谱,并具有自定义内存路径和时间戳等功能,用于捕获通过语言模型进行的交互。
MCP Jupiter
一个模型上下文协议服务器,使 Claude 能够通过 Jupiter 的 API 执行 Solana 代币兑换,包括获取报价、构建交易以及在 Solana 区块链上发送兑换交易。
MCP
一个使用 Claude 和 DuckDuckGo 的 Minecraft 服务器。 (Yī gè shǐyòng Claude hé DuckDuckGo de Minecraft fúwùqì.)
Clarity Data Export MCP Server
A Model Context Protocol server that lets you fetch Microsoft Clarity analytics data through Claude for Desktop or other MCP-compatible clients, with support for filtering by dimensions and retrieving various metrics.
MarkLogic MCP Server by CData
This read-only MCP Server allows you to connect to MarkLogic data from Claude Desktop through CData JDBC Drivers. Free (beta) read/write servers available at https://www.cdata.com/solutions/mcp
BMAD-MCP
Orchestrates complete agile development workflows from product requirements to QA testing through role-based stages (PO → Architect → SM → Dev → Review → QA). Manages workflow state, generates role-specific prompts, and saves artifacts while integrating with multiple AI engines for comprehensive project delivery.
mcp-ipfs
🪐 MCP IPFS 服务器 该服务器使语言模型 🤖 和其他 MCP 客户端能够管理 storacha.network 空间、上传/下载数据、管理委托,并通过无缝封装 w3 命令来执行各种其他任务。
mcp-agent-tool-adapter
使用现代 Agent 框架将 MCP 工具转换为协作式推理 Agent。
Tableau MCP Server
Enables interaction with Tableau Cloud and Tableau Server through the REST API, supporting workbook management, view queries, extract refreshes, and content search operations.
ChainGPT MCP
Enables AI agents to access crypto-related information including latest news, prices, and market trends through ChainGPT capabilities.
Canvas Assignment Assistant
Enables interaction with Canvas LMS courses and assignments directly from your LLM, allowing you to retrieve, search, and summarize course information, check due dates, and access assignment details without leaving your AI assistant.
TypeScript Prompt MCP Server
Okay, I understand. Here are some pre-defined prompt templates you can use for AI assistants to generate comprehensive plans for TypeScript projects, API architectures, and GitHub workflows. I've included variations and options to make them more flexible. **1. TypeScript Project Plan:** * **Template 1 (General):** ``` Create a comprehensive plan for a TypeScript project named "[Project Name]" that aims to [briefly describe the project's purpose]. The plan should include: * **Project Goals and Objectives:** Clearly defined goals and measurable objectives. * **Technology Stack:** Recommended libraries, frameworks, and tools (e.g., React, Angular, Node.js, Express, testing frameworks, linting tools). Justify each choice. * **Project Structure:** A proposed directory structure and module organization. * **Coding Standards and Conventions:** Guidelines for code style, naming conventions, and documentation. * **Testing Strategy:** A plan for unit, integration, and end-to-end testing. Specify testing frameworks and methodologies. * **Build and Deployment Process:** Steps for building, packaging, and deploying the application. Include CI/CD considerations. * **Dependencies Management:** How dependencies will be managed (e.g., npm, yarn, pnpm). * **Error Handling and Logging:** Strategies for handling errors and logging information. * **Security Considerations:** Potential security vulnerabilities and mitigation strategies. * **Scalability Considerations:** How the application can be scaled to handle increased load. * **Future Enhancements:** Potential future features or improvements. * **Initial Setup Instructions:** Step-by-step instructions for setting up the development environment. The target audience for this project is [describe the target audience, e.g., small businesses, individual users, enterprise clients]. The project should be [describe desired qualities, e.g., maintainable, scalable, performant, secure]. ``` * **Template 2 (Specific Framework):** ``` Develop a detailed plan for a TypeScript project using [Framework Name] (e.g., React, Angular, NestJS) to build [briefly describe the application]. The plan should cover: * **Project Goals and Objectives:** Clearly defined goals and measurable objectives. * **Framework-Specific Architecture:** How to leverage [Framework Name]'s architecture (e.g., components, services, modules) for this project. * **State Management:** Recommended state management solution (e.g., Redux, Zustand, Context API) and justification. * **Routing:** How routing will be implemented (e.g., React Router, Angular Router). * **Data Fetching:** Strategies for fetching data from APIs (e.g., Axios, Fetch API, GraphQL). * **UI Component Library:** Recommended UI component library (e.g., Material UI, Ant Design, Chakra UI) and justification. * **Testing Strategy:** A plan for unit, integration, and end-to-end testing, specific to [Framework Name]. Specify testing frameworks and methodologies (e.g., Jest, Cypress, Testing Library). * **Build and Deployment Process:** Steps for building, packaging, and deploying the application, optimized for [Framework Name]. Include CI/CD considerations. * **Dependencies Management:** How dependencies will be managed (e.g., npm, yarn, pnpm). * **Error Handling and Logging:** Strategies for handling errors and logging information. * **Security Considerations:** Potential security vulnerabilities and mitigation strategies. * **Scalability Considerations:** How the application can be scaled to handle increased load. * **Future Enhancements:** Potential future features or improvements. * **Initial Setup Instructions:** Step-by-step instructions for setting up the development environment. The target audience for this project is [describe the target audience, e.g., small businesses, individual users, enterprise clients]. The project should be [describe desired qualities, e.g., maintainable, scalable, performant, secure]. ``` * **Template 3 (Backend API):** ``` Create a comprehensive plan for a TypeScript backend API project named "[API Name]" that will [briefly describe the API's purpose]. The plan should include: * **API Goals and Objectives:** Clearly defined goals and measurable objectives. * **Technology Stack:** Recommended libraries, frameworks, and tools (e.g., Node.js, Express, NestJS, database, ORM, testing frameworks, linting tools). Justify each choice. * **API Architecture:** A proposed architecture (e.g., REST, GraphQL, gRPC). Explain the chosen architecture's benefits for this project. * **Database Design:** A high-level database schema and data model. Specify the database technology (e.g., PostgreSQL, MongoDB, MySQL). * **Authentication and Authorization:** A plan for securing the API, including authentication and authorization mechanisms (e.g., JWT, OAuth). * **API Documentation:** How the API will be documented (e.g., OpenAPI/Swagger). * **Error Handling and Logging:** Strategies for handling errors and logging information. * **Testing Strategy:** A plan for unit, integration, and end-to-end testing. Specify testing frameworks and methodologies. * **Build and Deployment Process:** Steps for building, packaging, and deploying the API. Include CI/CD considerations. * **Dependencies Management:** How dependencies will be managed (e.g., npm, yarn, pnpm). * **Security Considerations:** Potential security vulnerabilities and mitigation strategies (e.g., input validation, rate limiting). * **Scalability Considerations:** How the API can be scaled to handle increased load (e.g., load balancing, caching). * **Rate Limiting:** A strategy for rate limiting API requests. * **Monitoring and Alerting:** How the API will be monitored and how alerts will be generated. * **Future Enhancements:** Potential future features or improvements. * **Initial Setup Instructions:** Step-by-step instructions for setting up the development environment. The API will be consumed by [describe the consumers of the API, e.g., web applications, mobile apps, other APIs]. The API should be [describe desired qualities, e.g., performant, secure, reliable, well-documented]. ``` **2. API Architecture Plan:** * **Template 1 (General):** ``` Design a robust and scalable API architecture for [briefly describe the application or system the API will support]. The architecture should address the following requirements: * **API Style:** Choose an appropriate API style (e.g., REST, GraphQL, gRPC) and justify the choice based on the project's needs. * **Data Format:** Specify the data format (e.g., JSON, XML, Protocol Buffers). * **Authentication and Authorization:** Describe the authentication and authorization mechanisms (e.g., JWT, OAuth, API keys). Consider different user roles and permissions. * **Rate Limiting:** Implement a rate limiting strategy to prevent abuse and ensure fair usage. * **Versioning:** Plan for API versioning to allow for future changes without breaking existing clients. * **Error Handling:** Define a consistent error handling strategy, including error codes and messages. * **Documentation:** Specify how the API will be documented (e.g., OpenAPI/Swagger, Postman collections). * **Caching:** Implement caching strategies to improve performance and reduce load on the backend. * **Security:** Address common security vulnerabilities, such as injection attacks, cross-site scripting (XSS), and cross-site request forgery (CSRF). * **Scalability:** Design the architecture to be scalable to handle increasing traffic and data volume. Consider load balancing, horizontal scaling, and database optimization. * **Monitoring and Logging:** Implement monitoring and logging to track API performance and identify potential issues. * **Deployment:** Describe the deployment strategy (e.g., cloud-based, on-premise). * **Technology Stack:** Recommend specific technologies and tools for implementing the API (e.g., Node.js, Express, NestJS, databases, message queues). The API will be used by [describe the consumers of the API]. The key performance indicators (KPIs) for the API are [list the KPIs, e.g., response time, error rate, throughput]. ``` * **Template 2 (Microservices):** ``` Design a microservices-based API architecture for [briefly describe the application or system]. The architecture should address the following: * **Service Decomposition:** Identify the key services and their responsibilities. Explain the rationale behind the service decomposition. * **Communication:** Specify the communication protocols between services (e.g., REST, gRPC, message queues). Justify the choice. * **Service Discovery:** Implement a service discovery mechanism to allow services to locate each other. * **API Gateway:** Design an API gateway to handle external requests and route them to the appropriate services. * **Authentication and Authorization:** Implement authentication and authorization across the microservices. * **Data Management:** Describe how data will be managed across the microservices. Consider data consistency and eventual consistency. * **Monitoring and Logging:** Implement centralized monitoring and logging for all microservices. * **Deployment:** Describe the deployment strategy for the microservices (e.g., containers, Kubernetes). * **Fault Tolerance:** Design the architecture to be fault-tolerant and resilient to failures. * **Technology Stack:** Recommend specific technologies and tools for implementing the microservices (e.g., Docker, Kubernetes, message queues, databases). The system will handle [describe the scale and complexity of the system]. The key challenges in this architecture are [list the key challenges, e.g., data consistency, distributed tracing, security]. ``` **3. GitHub Workflow Plan:** * **Template 1 (General):** ``` Create a GitHub workflow plan for a [TypeScript/JavaScript/Python/etc.] project named "[Project Name]". The plan should include: * **Branching Strategy:** Define a branching strategy (e.g., Gitflow, GitHub Flow, Trunk-Based Development). Explain the rationale behind the chosen strategy. * **Pull Request Process:** Describe the pull request process, including code review guidelines and approval requirements. * **Continuous Integration (CI):** Implement CI to automatically build, test, and lint the code on every pull request and push. Specify the CI tools (e.g., GitHub Actions, Jenkins, CircleCI). * **Automated Testing:** Integrate automated testing into the CI pipeline. Specify the testing frameworks and types of tests (e.g., unit tests, integration tests, end-to-end tests). * **Code Linting and Formatting:** Enforce code style and formatting using linters and formatters (e.g., ESLint, Prettier). * **Code Coverage:** Track code coverage to ensure adequate test coverage. * **Continuous Deployment (CD):** Implement CD to automatically deploy the application to production after successful CI. Specify the deployment environment and strategy. * **Release Management:** Define a release management process, including versioning and tagging. * **Issue Tracking:** Use GitHub Issues to track bugs, features, and tasks. * **Security Scanning:** Integrate security scanning tools to identify vulnerabilities in the code and dependencies. * **Documentation Generation:** Automate the generation of documentation from the code. * **Dependency Management:** Automate dependency updates and vulnerability scanning. The project is [describe the project's size and complexity]. The goal of the workflow is to [describe the goals, e.g., improve code quality, automate deployments, reduce errors]. ``` * **Template 2 (GitHub Actions Specific):** ``` Design a GitHub Actions workflow for a [TypeScript/JavaScript/Python/etc.] project named "[Project Name]". The workflow should: * **Trigger:** Specify the triggers for the workflow (e.g., pull requests, pushes to main branch, scheduled events). * **Jobs:** Define the jobs in the workflow, including their dependencies and execution order. * **Steps:** Specify the steps in each job, including the commands to execute and the actions to use. * **Environment Variables:** Use environment variables to configure the workflow. * **Secrets:** Store sensitive information (e.g., API keys, passwords) as secrets. * **Caching:** Use caching to speed up the workflow. * **Artifacts:** Store build artifacts (e.g., compiled code, documentation) for later use. * **Notifications:** Send notifications on workflow completion or failure. * **Error Handling:** Implement error handling to gracefully handle failures. * **Specific Tasks:** Include steps for [list specific tasks, e.g., running unit tests, building the application, deploying to AWS, publishing to npm]. Provide a YAML configuration file for the GitHub Actions workflow. The project is [describe the project's size and complexity]. The goal of the workflow is to [describe the goals, e.g., automate deployments, improve code quality, reduce errors]. ``` **Key Considerations for Using These Templates:** * **Be Specific:** The more specific you are in your prompt, the better the results will be. Provide as much context as possible about the project, its goals, and its requirements. * **Iterate:** Don't expect the AI to generate the perfect plan on the first try. Review the output carefully and iterate on the prompt to refine the plan. * **Customize:** These are just templates. Customize them to fit the specific needs of your project. * **Review and Validate:** Always review and validate the AI-generated plan to ensure that it is accurate, complete, and feasible. Don't blindly trust the AI. * **Consider the AI's Limitations:** AI assistants are good at generating text, but they may not have a deep understanding of software development principles or best practices. Use your own expertise to evaluate the AI's suggestions. By using these templates and following these guidelines, you can effectively leverage AI assistants to generate comprehensive plans for your TypeScript projects, API architectures, and GitHub workflows. Good luck!