mcp-installer MCP Server

What does “mcp-installer” MCP Server do?

The mcp-installer MCP Server is a specialized Model Context Protocol (MCP) server designed to streamline and automate the installation of other MCP servers. By acting as an installation manager, it allows AI assistants and users to easily deploy additional MCP servers from npm or PyPi repositories. This enhances the development workflow by enabling dynamic expansion of available AI tools and integrations without manual setup. With the mcp-installer, tasks such as fetching, installing, and configuring various MCP-compatible servers become seamless, allowing developers and AI agents to quickly access new capabilities, such as database queries, file management, or API interactions, simply by issuing installation commands. The server requires npx for Node.js-based servers and uv for Python-based servers, ensuring broad compatibility and flexibility.

List of Prompts

No prompt templates are documented in the available files or README.

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List of Resources

No resources are explicitly mentioned in the available files or README.

List of Tools

No tool implementations are documented or listed in the available files or README. The likely tool is “install MCP server,” but this is not explicitly described in the code or documentation.

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Use Cases of this MCP Server

• Automated Installation of MCP Servers: Simplifies the process of deploying new MCP servers from npm or PyPi, reducing manual effort and potential for configuration errors.
• Rapid Expansion of AI Capabilities: Enables developers and AI assistants to quickly add new functionalities (e.g., database, file, or API integrations) by installing compatible MCP servers on demand.
• Centralized MCP Management: Acts as a hub for managing multiple MCP servers, making updates and maintenance more straightforward.
• Streamlined Onboarding: Lowers the barrier for new users to set up a full AI development environment with minimal knowledge of underlying server infrastructure.
• Integration with AI Assistants: Allows AI agents (like Claude) to autonomously expand their toolset by requesting the installation of new MCP servers as needed.

How to set it up

Windsurf

1. Prerequisites: Ensure you have Node.js installed, along with npx for Node.js MCP servers and uv for Python MCP servers.
2. Locate Configuration: Open your Windsurf configuration file.
3. Add mcp-installer MCP Server:

   {
     "mcpServers": {
       "mcp-installer": {
         "command": "npx",
         "args": ["@anaisbetts/mcp-installer@latest"]
       }
     }
   }
   

4. Save and Restart: Save your configuration and restart Windsurf.
5. Verify: Confirm that “mcp-installer” appears among your available MCP servers.

Claude

1. Prerequisites: Make sure Node.js, npx, and uv are installed.
2. Access Configuration: Open the Claude configuration file.
3. Add mcp-installer:

   {
     "mcpServers": {
       "mcp-installer": {
         "command": "npx",
         "args": ["@anaisbetts/mcp-installer@latest"]
       }
     }
   }
   

4. Save and Restart: Apply changes and restart Claude.
5. Verify: Check Claude’s interface for the “mcp-installer” MCP server.

Cursor

1. Install Prerequisites: Ensure Node.js, npx, and uv are present on your system.
2. Edit Configuration: Locate the Cursor configuration file.
3. Insert Configuration:

   {
     "mcpServers": {
       "mcp-installer": {
         "command": "npx",
         "args": ["@anaisbetts/mcp-installer@latest"]
       }
     }
   }
   

4. Restart Cursor: Restart the Cursor application.
5. Check Setup: Confirm the mcp-installer is listed as an MCP server.

Cline

1. Prepare Environment: Install Node.js, npx, and uv.
2. Open Config File: Access Cline’s configuration file.
3. Configure mcp-installer:

   {
     "mcpServers": {
       "mcp-installer": {
         "command": "npx",
         "args": ["@anaisbetts/mcp-installer@latest"]
       }
     }
   }
   

4. Save and Restart: Save your configuration and restart Cline.
5. Validate: Ensure mcp-installer is running within Cline.

Securing API Keys:
Store API keys using environment variables for enhanced security. Example configuration:

{
  "mcpServers": {
    "mcp-installer": {
      "command": "npx",
      "args": ["@anaisbetts/mcp-installer@latest"],
      "env": {
        "MY_API_KEY": "${MY_API_KEY}"
      },
      "inputs": {
        "apiKey": "${MY_API_KEY}"
      }
    }
  }
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "mcp-installer": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “mcp-installer” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Our opinion

The mcp-installer MCP server provides a valuable automation layer for installing other MCP servers, which is a unique and powerful capability. However, the lack of documentation on prompt templates, resources, and tools limits its transparency and usability for more advanced workflows. With clearer information and richer documentation, its usefulness would rate higher, but as it stands, it’s a strong utility for expanding MCP capabilities with minimal setup.
Rating: 6/10

MCP Score