forevervm MCP Server

What does “forevervm” MCP Server do?

The forevervm MCP (Model Context Protocol) Server is designed as a bridge between AI assistants and external data sources, APIs, or services. By acting as an intermediary, it enables AI-driven workflows to integrate seamlessly with various backend functionalities, such as database queries, file management, or API interactions. This capability empowers developers to augment their AI systems with real-time data access, enriched context, and operational tools, thereby streamlining development processes and unlocking new levels of automation and intelligence. The forevervm MCP Server is particularly valuable for scenarios where intelligent agents must interact dynamically with the digital environment, improving both productivity and the range of tasks that can be handled autonomously.

List of Prompts

No information about prompt templates was found in the provided repository files.

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List of Resources

No information about MCP resources exposed by the forevervm MCP Server was found in the available files.

List of Tools

No information about tools provided in server.py or equivalent was found in the available files.

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Use Cases of this MCP Server

No explicit use cases were documented in the provided files. Common uses for MCP servers generally include:

• Database management: Allowing AI agents to perform queries or updates on databases directly via the MCP interface.
• API integration: Facilitating secure and streamlined calls to external APIs for data enrichment or task automation.
• File operations: Enabling reading, writing, or updating files as part of development or workflow automation.
• Development workflow automation: Integrating with CI/CD systems or project management tools to automate repetitive tasks.
• Codebase exploration: Empowering AI-driven code review, search, or documentation generation within large codebases.

How to set it up

Windsurf

1. Ensure Node.js and npm are installed.
2. Open your Windsurf configuration file (windsurf.json or equivalent).
3. Add the forevervm MCP server to the mcpServers section:

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

4. Save the configuration file.
5. Restart Windsurf and verify the MCP server is running.

Claude

1. Confirm prerequisites such as Node.js are installed.
2. Locate Claude’s configuration file.
3. Insert the forevervm MCP server in the mcpServers array:

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

4. Save and restart Claude.
5. Check logs to ensure the MCP server is active.

Cursor

1. Install Node.js if not already present.
2. Open Cursor’s main configuration file.
3. Add forevervm MCP server using:

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

4. Save and restart Cursor.
5. Verify the server connection from Cursor’s interface.

Cline

1. Make sure Node.js is available.
2. Locate your Cline configuration file.
3. Configure the forevervm MCP server in the mcpServers object:

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

4. Save configuration and restart Cline.
5. Confirm the server is working by running a test command.

Securing API Keys

Use environment variables to manage sensitive credentials. Example configuration:

{
  "mcpServers": {
    "forevervm": {
      "command": "npx",
      "args": ["@forevervm/mcp-server@latest"],
      "env": {
        "API_KEY": "${API_KEY}"
      },
      "inputs": {
        "apiKey": "${API_KEY}"
      }
    }
  }
}

Replace API_KEY with your actual key and ensure your environment is configured accordingly.

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:

{
  "forevervm": {
    "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 “forevervm” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Between these two tables, the forevervm MCP Server appears to lack documentation or explicit implementation for resources, prompts, and tools in the provided directory. The setup instructions and API key management are well-covered, but core MCP features are not evident in the available files. Based on this, we would rate this MCP server a 2/10 for completeness and developer usability at this stage.

MCP Score