MCP Server
M

MCP Server

The MCP Server Dashboard is a unified management platform that simplifies the management and scaling of multiple MCP servers through flexible streaming HTTP endpoints. It supports on-demand access to all servers, a single server, or a logically grouped set of servers, and provides a centralized web management interface.
2.5 points
3.5K

What is the MCP Server Dashboard?

The MCP Server Dashboard is a centralized management platform dedicated to managing and scaling multiple Model Context Protocol (MCP) servers. It provides an elegant web interface that allows you to easily monitor, configure, and control all MCP servers without complex command-line operations. Whether you are using MCP servers in a local development environment or a production environment, this dashboard provides a unified management experience.

How to use the MCP Server Dashboard?

Using the MCP Server Dashboard is very simple: First, deploy the platform via Docker or a local installation. Then, add your MCP servers through a configuration file. After deployment, you can manage all servers through the web interface and connect AI clients (such as Claude Desktop, Cursor, etc.) to your MCP servers via a unified HTTP endpoint. The platform supports flexible access methods, including accessing all servers, specific server groups, or a single server.

Applicable scenarios

The MCP Server Dashboard is particularly suitable for the following scenarios: Development teams that need to manage multiple MCP servers simultaneously; Organizations that wish to isolate MCP tools for different projects or environments; Applications that need to provide a unified tool access interface for AI assistants; and Users who want to simplify MCP server operation and management through a web interface.

Main features

Comprehensive MCP server support
Seamlessly integrate any MCP server with extremely low configuration requirements. Supports adding and managing various MCP servers through a simple JSON configuration file.
Centralized management console
Monitor the real-time status and performance metrics of all servers from one interface through an elegant web UI. No need to switch between different terminals or tools.
Flexible protocol compatibility
Fully supports stdio and SSE MCP protocols, ensuring compatibility with various AI clients and tools.
Hot-swappable configuration
Dynamically add, delete, or update server configurations at runtime without downtime. Configuration changes take effect immediately.
Group-based access control
Organize servers using custom groups and manage access permissions. You can create independent server groups for different teams or projects.
Secure authentication system
Built-in user management, supporting role-based access control based on JWT and bcrypt. Ensures that only authorized users can access management functions.
Docker-ready deployment
Provides containerized images for fast deployment. Includes Docker Compose configuration to start the full environment with one click.
Intelligent routing (experimental)
Use vector semantic search to automatically find the most relevant tools for any task. Implements intelligent tool discovery based on PostgreSQL and pgvector.
Advantages
Unified management interface: Manage all MCP servers through a single web interface, simplifying operation and maintenance work.
Flexible access methods: Supports global access, group access, and single-server access to meet different usage scenarios.
Easy to deploy: Provides Docker images and Docker Compose configuration for quick start-up.
Real-time monitoring: View server status and performance in real-time to quickly identify problems.
Secure and reliable: Built-in user authentication and permission control to protect server configuration security.
Highly scalable: Supports hot-swappable configuration to easily add new servers.
Limitations
Learning curve: Users unfamiliar with the MCP protocol may need some time to learn.
Resource consumption: Running multiple MCP servers may require more system resources.
Client compatibility: Some AI clients may have limited support for SSE endpoints.
Configuration complexity: Advanced features (such as intelligent routing) require additional components (PostgreSQL, Redis).

How to use

Configure MCP servers
Create an mcp_settings.json configuration file to define the MCP servers you want to manage. Each server needs to specify commands, parameters, and environment variables.
Deploy the Dashboard
Use Docker Compose to quickly deploy the MCP Server Dashboard. You can choose a basic deployment or a full deployment that includes Nginx, Redis, and PostgreSQL.
Access the management console
Open a browser and access http://localhost:3000. Log in using the default credentials (admin/admin123). It is recommended to change the password after the first login.
Configure server groups
Create server groups in the console to organize related servers together. Groups can be classified by project, team, or function.
Connect AI clients
Configure MCP connections in AI clients (such as Claude Desktop, Cursor) and use the corresponding HTTP endpoints to connect to your servers.

Usage examples

Configure a toolset for a development team
A development team needs to provide a set of development-related tools for their AI assistant, including code search, document query, and API testing tools.
Configure a knowledge base tool for customer support
The customer support team needs quick access to product documentation, frequently asked questions, and customer history to provide efficient support services.
Integrate data analysis tools for a research team
A research team needs to access multiple data sources, analysis tools, and visualization services for data analysis and report generation.

Frequently Asked Questions

Which MCP servers does the MCP Server Dashboard support?
How to change the default administrator password?
What conditions are required for the intelligent routing function?
If the server name and group name are the same, which one will be accessed?
How to solve the problem of the Nginx reverse proxy?
How can Windows users perform local development?
How to add a new MCP server?
Which AI clients are supported?

Related resources

GitHub repository
Source code and latest version of the MCP Server Dashboard
Model Context Protocol documentation
Official specification and documentation of the MCP protocol
Docker documentation
Official documentation of Docker containerization technology
List of MCP servers
Collection of official and community MCP servers
Chinese README
Chinese version of the MCP Server Dashboard documentation

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "amap": {
      "command": "npx",
      "args": ["-y", "@amap/amap-maps-mcp-server"],
      "env": {
        "AMAP_MAPS_API_KEY": "your-api-key"
      }
    },
    "playwright": {
      "command": "npx",
      "args": ["@playwright/mcp@latest", "--headless"]
    },
    "fetch": {
      "command": "uvx",
      "args": ["mcp-server-fetch"]
    },
    "slack": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-slack"],
      "env": {
        "SLACK_BOT_TOKEN": "your-bot-token",
        "SLACK_TEAM_ID": "your-team-id"
      }
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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