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MCP Orchestrator Server

Source

small MCP server for orchestrating tasks across LLM instances

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Overview

The MCP Orchestrator Server is a lightweight server designed for orchestrating tasks across multiple Large Language Model (LLM) instances, providing essential task management and coordination capabilities. ## How to use MCP Orchestrator Server? To use the MCP Orchestrator Server, install it using npm, build the project, and utilize the API to create and manage tasks across distributed systems. ## Key features of MCP Orchestrator Server? - Task management with dependency enforcement - Multi-instance coordination - Persistent task storage - Cycle detection to prevent dependency loops - Comprehensive tool documentation and enhanced state management ## Use cases of MCP Orchestrator Server?

  1. Managing tasks in a distributed machine learning environment
  2. Coordinating operations across multiple LLMs for complex workflows
  3. Facilitating process automation where task dependencies need to be tracked ## FAQ from MCP Orchestrator Server? - Can I track the status of tasks? > Yes! The server provides built-in task status tracking features. - Is the MCP Orchestrator Server suitable for production use? > Yes, it is designed for stable task management and is suitable for production environments. - How do I handle task creation? > You can create tasks using the provided API with specific parameters for dependencies and descriptions.

Add to your AI client

Use these steps to connect MCP Orchestrator Server in Cursor, Claude, VS Code, and other MCP-compatible apps. The same JSON appears in the Use with menu above for one-click copy.

Cursor

Add this to your .cursor/mcp.json file in your project root, then restart Cursor.

.cursor/mcp.json

{
  "mcpServers": {
    "orchestrator-server-mokafari": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-orchestrator-server-mokafari"
      ]
    }
  }
}

Claude Desktop

Add this server entry to the mcpServers object in your Claude Desktop config, then restart the app.

~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)

{
  "mcpServers": {
    "orchestrator-server-mokafari": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-orchestrator-server-mokafari"
      ]
    }
  }
}

Claude Code

Add this to your project's .mcp.json file. Claude Code will detect it automatically.

.mcp.json (project root)

{
  "mcpServers": {
    "orchestrator-server-mokafari": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-orchestrator-server-mokafari"
      ]
    }
  }
}

VS Code (Copilot)

Add this to your .vscode/mcp.json file. Requires the GitHub Copilot extension with MCP support enabled.

.vscode/mcp.json

{
  "servers": {
    "orchestrator-server-mokafari": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-orchestrator-server-mokafari"
      ]
    }
  }
}

Windsurf

Add this to your Windsurf MCP config file, then restart Windsurf.

~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "orchestrator-server-mokafari": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-orchestrator-server-mokafari"
      ]
    }
  }
}

Cline

Open Cline settings, navigate to MCP Servers, and add this server configuration.

Cline MCP Settings (via UI)

{
  "mcpServers": {
    "orchestrator-server-mokafari": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-orchestrator-server-mokafari"
      ]
    }
  }
}
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