MCP-Server-Creator MCP Server

What does “MCP-Server-Creator” MCP Server do?

The MCP-Server-Creator MCP Server is a meta-server designed to facilitate the creation of other Model Context Protocol (MCP) servers. Acting as a powerful development tool, it enables users to dynamically generate FastMCP server configurations and Python code without manual boilerplate. With an integrated tool builder, resource manager, and code generation capabilities, MCP-Server-Creator streamlines workflows for developers looking to connect AI assistants to external data sources, APIs, or services. This server empowers tasks such as adding custom tools, managing static and dynamic resources, and exporting runnable Python code, thereby enhancing productivity for teams building complex AI-enabled development environments.

List of Prompts

• No explicit prompt templates are listed in the provided repository documentation or files.

List of Resources

• No explicit MCP resources are detailed in the provided repository documentation or files.

List of Tools

• Dynamic Server Creation: Allows users to create new MCP server configurations on the fly.
• Tool Builder: Provides a mechanism to add custom tools with customizable parameters, return types, and implementations.
• Resource Manager: Lets users add both static and dynamic resources with template support.
• Code Generation: Generates complete, runnable Python code for newly defined MCP servers.
• File Export: Enables saving generated servers directly to Python files for deployment or sharing.

Use Cases of this MCP Server

• Rapid Prototyping of MCP Servers: Quickly design and deploy custom MCP servers tailored to specific integration or workflow requirements.
• Custom Tooling for AI Assistants: Develop and add new tools for AI agents, enabling bespoke interactions with databases, files, or external APIs.
• Resource Management: Efficiently manage and serve static or dynamic resources as context for LLM (Large Language Model) interactions.
• Automated Code Generation: Automatically produce Python server code, reducing manual errors and accelerating deployment.
• Template-Based Server Deployment: Utilize example templates to create standardized server configurations for recurring development needs.

How to set it up

Windsurf

1. Ensure you have Node.js and Windsurf installed.
2. Locate your Windsurf configuration file (e.g., windsurf.config.json).
3. Add the MCP-Server-Creator MCP server using a JSON snippet:

   {
     "mcpServers": {
       "mcp-server-creator": {
         "command": "python",
         "args": ["-m", "mcp_server_creator"]
       }
     }
   }
   

4. Save the configuration file and restart Windsurf.
5. Verify the MCP server appears in your available servers.

Claude

1. Install MCP-Server-Creator with pip:
   pip install mcp-server-creator
2. Locate your Claude Desktop configuration (e.g., claude_desktop_config.json).
3. Add the MCP-Server-Creator server:

   {
     "mcpServers": {
       "mcp-server-creator": {
         "command": "python",
         "args": ["-m", "mcp_server_creator"]
       }
     }
   }
   

4. Save and restart Claude Desktop.
5. Confirm the server runs (refer to CLAUDE.md and claude_desktop_config.json for examples).

Cursor

1. Ensure Node.js and Cursor are installed.
2. Locate your Cursor configuration file.
3. Insert the MCP-Server-Creator server:

   {
     "mcpServers": {
       "mcp-server-creator": {
         "command": "python",
         "args": ["-m", "mcp_server_creator"]
       }
     }
   }
   

4. Save the config and restart Cursor.
5. Confirm the MCP server is recognized in the UI.

Cline

1. Install MCP-Server-Creator with pip:
   pip install mcp-server-creator
2. Find the Cline configuration file.
3. Add MCP-Server-Creator as follows:

   {
     "mcpServers": {
       "mcp-server-creator": {
         "command": "python",
         "args": ["-m", "mcp_server_creator"]
       }
     }
   }
   

4. Save your changes and restart Cline.
5. Ensure the new server is running correctly.

Securing API Keys

To secure API keys and other secrets, use environment variables in your configuration. Example:

{
  "mcpServers": {
    "mcp-server-creator": {
      "command": "python",
      "args": ["-m", "mcp_server_creator"],
      "env": {
        "MY_API_KEY": "${MY_API_KEY}"
      },
      "inputs": {
        "api_key": "${MY_API_KEY}"
      }
    }
  }
}

Replace MY_API_KEY with your actual key, and ensure it is set in your environment.

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-Server-Creator": {
    "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-Server-Creator” to the actual name of your MCP server and replace the URL with your MCP server endpoint.

Overview

Our opinion

MCP-Server-Creator is a highly specialized server for MCP development, excelling at tool and server generation but lacking explicit prompt and resource definitions. It is best suited for technical users seeking to bootstrap or template new MCP servers. Documentation is clear for installation, but lacking in resource and prompt extensibility examples.

MCP Score

Rating:
Based on the above, this MCP server rates at 6/10. It provides robust server and tool creation features but would benefit from richer prompt/resource support and more usage documentation for less technical users.