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MCPHubs: Explore Innovations, Connect Builders - MCP Implementation

MCPHubs: Explore Innovations, Connect Builders

Discover Anthropic's Model Context Protocol (MCP) projects in one hub: explore innovations, connect with builders, and expand AI's possibilities seamlessly.

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About MCPHubs

What is MCPHubs: Explore Innovations, Connect Builders?

MCPHubs is a platform dedicated to showcasing projects built around Anthropic's Model Context Protocol (MCP). It serves as a centralized hub for developers and builders to discover, analyze, and contribute to MCP-related initiatives. The site leverages modern web technologies like Next.js and AI-driven analysis to curate and evaluate projects, providing actionable insights for the community.

How to Use MCPHubs: Explore Innovations, Connect Builders?

Explore the platform by visiting the homepage to browse curated MCP projects. Filter or search for specific initiatives, then dive into detailed project pages for technical documentation, contributor information, and AI-generated analysis. Developers can also submit their own projects via the contribution portal, while researchers can use the platform’s tools to track trends and benchmark progress.

MCPHubs Features

Key Features of MCPHubs: Explore Innovations, Connect Builders?

Core features include:

  • Smart Curation: Automatically aggregates MCP projects from GitHub using custom APIs, ensuring up-to-date listings.
  • AI Analysis: Uses machine learning to assess project complexity, innovation potential, and alignment with MCP standards.
  • Dynamic Interface: Responsive design optimized for coders to work seamlessly across devices.
  • Community Tools: Discussion forums, version comparison tools, and real-time contribution tracking.

Use Cases of MCPHubs: Explore Innovations, Connect Builders?

Users leverage MCPHubs in scenarios like:

– A developer seeking inspiration for their next MCP-based project, using the analysis tool to evaluate project viability.

– A startup comparing competing solutions to choose a framework for their AI model deployment.

– Academics mapping the evolution of MCP adoption across industries through the platform’s analytics dashboard.

MCPHubs FAQ

FAQ from MCPHubs: Explore Innovations, Connect Builders?

Q: How do I contribute a project?
Submit via the "Contribute" tab with your GitHub repository URL. Projects are validated for MCP compliance within 48 hours.

Q: Is there a cost to use the platform?
Core features are free. Advanced analytics and enterprise collaboration tools require a subscription.

Q: Can I customize search filters?
Yes. Refine results by technology stack, license type, last update date, and AI-scored innovation metrics.

Q: What happens if my project is flagged?
We provide a review portal where creators can address compliance issues or technical discrepancies.

Q: How do I contact support?
Visit support portal for ticket submission or join our Discord community for real-time help.

Content

MCPHubs - Model Context Protocol Projects Hub

MCPHubs 是一个展示与 Anthropic 的 Model Context Protocol (MCP) 相关项目的网站。该网站使用 Next.js 构建，提供了以下功能：

  • 从 GitHub 检索与 MCP 相关的项目
  • 使用 AI 分析项目内容，评估与 MCP 的相关性
  • 展示项目列表和详细信息
  • 提供项目的 README 内容和相关分析

技术栈

  • Next.js 15
  • TypeScript
  • Tailwind CSS
  • React Icons
  • Axios (用于 API 请求)
  • Google Cloud Vertex AI (Gemini Pro 模型，用于 AI 分析)
  • React Markdown (用于渲染 README)

特性

  • 环境自适应代理：在开发环境自动使用代理解决 CORS 问题，生产环境直接调用 API
  • GitHub API 集成：检索与 MCP 相关的项目
  • AI 分析：使用 Google Gemini Pro 评估项目与 MCP 的相关性
  • 响应式设计：适配各种设备尺寸

本地开发

  1. 克隆仓库
git clone https://github.com/yourusername/mcphubs.git
cd mcphubs
  1. 安装依赖
npm install
  1. 配置环境变量

创建 .env.local 文件并添加以下内容：

# GitHub API Token (可选，但推荐使用以避免 API 速率限制)
GITHUB_TOKEN=your_github_token_here

# Google Cloud Vertex AI 配置
GOOGLE_CLOUD_PROJECT=your-project-id
GOOGLE_CLOUD_LOCATION=us-central1
GOOGLE_APPLICATION_CREDENTIALS=./google-credentials.json
VERTEX_LOCATION=us-central1
  1. 配置 Google Cloud 服务账号

将您的 Google Cloud 服务账号凭据文件（JSON 格式）放在项目根目录下，文件名与 GOOGLE_APPLICATION_CREDENTIALS 环境变量中指定的名称一致。

如果您还没有服务账号，可以按照以下步骤创建：

  • 前往 Google Cloud Console
  • 选择您的项目
  • 导航到 "IAM & Admin" > "Service Accounts"
  • 创建新的服务账号，并授予必要的权限（Vertex AI 使用者）
  • 创建并下载 JSON 密钥文件
  • 将文件放在项目根目录下
  1. 启动开发服务器
./start-dev.sh
  1. 在浏览器中访问 http://localhost:3001 (或控制台显示的其他端口)

代理配置说明

该项目具有环境自适应的代理配置：

  • 开发环境 ：自动启用 API 代理，解决本地开发时的 CORS 问题

    • GitHub API: /api/github/* → https://api.github.com/*
    • Vertex AI: /api/vertex/* → https://us-central1-aiplatform.googleapis.com/v1/*

  • 生产环境 ：自动禁用代理，直接调用外部 API

这种配置无需手动切换，系统会根据 NODE_ENV 环境变量自动决定是否使用代理。

部署

该项目可以部署到 Vercel、Netlify 或其他支持 Next.js 的平台。

部署时，请确保设置以下环境变量：

  • GITHUB_TOKEN
  • GOOGLE_CLOUD_PROJECT
  • GOOGLE_CLOUD_LOCATION
  • GOOGLE_APPLICATION_CREDENTIALS
  • VERTEX_LOCATION

对于云平台部署，您可能需要将 Google Cloud 凭据作为环境变量直接设置，而不是使用文件。

功能

  • 首页 ：展示 MCP 相关项目的列表
  • 项目详情页 ：展示单个项目的详细信息，包括：
    • 项目基本信息（名称、描述、星数等）
    • AI 分析的 MCP 相关性评分 (使用 Google Gemini Pro 模型)
    • 项目的关键特性和用例
    • 项目的 README 内容

许可证

MIT

Related MCP Servers & Clients

mcpmcp-server

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