About MCP Server Marketplace
MCP Server Marketplace is a web directory that collects MCP servers from GitHub for people looking to discover and compare them. Its dashboard supports search and sorting by repository stars.
Key features
- 01Search GitHub MCP servers
- 02Dashboard-style listings
- 03Sort by repository stars
- 04Responsive layout
Use cases
- 01Discover available MCP servers
- 02Browse servers by popularity
MCP support
It presents MCP servers collected from GitHub for discovery; the README does not describe an MCP service exposed to clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEMCP Server Marketplace
A web-based marketplace for MCP (Model Context Protocol) servers. This project aggregates popular MCP servers from GitHub, showcasing them in an easy-to-use dashboard format.
Features
- Search and display MCP servers from GitHub.
- Dashboard-style layout with responsive design.
- Sort repositories by stars for popular servers.
- Clean and simple UI with Tailwind CSS.
Tech Stack
- React: JavaScript library for building user interfaces.
- Vite: Fast build tool for modern web projects.
- Tailwind CSS: Utility-first CSS framework for styling.
- GitHub API: Used to fetch data from GitHub repositories.
- PostCSS: Used for processing Tailwind CSS.
Getting Started
To get started with this project, follow these steps:
Prerequisites
- Node.js (v14.x or higher)
- npm or yarn
Installation
-
Clone the repository to your local machine:
git clone https://github.com/yourusername/mcp-server-marketplace.git cd mcp-server-marketplace
Preview : 
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.