Skip to main content
Glama
ashcastelinocs124

Master MCP Orchestrator

Master MCP Orchestrator

A central MCP server that connects to multiple MCP servers and intelligently routes user queries to the appropriate MCP tools, then aggregates and returns responses.

πŸš€ Quick Start (Interactive CLI)

The easiest way to get started is with our interactive CLI:

python src/cli.py

The CLI will guide you through:

  • API key setup

  • MCP server discovery

  • MCP selection

  • Interactive query interface

See CLI_QUICKSTART.md for detailed instructions.

Related MCP server: MCPHub

Features

  • πŸ”Œ Multi-MCP Connection: Connect to multiple MCP servers simultaneously

  • πŸ€– AI-Powered Routing: Uses LLM to intelligently route queries (default)

  • 🧠 Intelligent Routing: Analyzes queries to determine which MCP(s) to call

  • πŸ” Tool Discovery: Automatically discovers available tools from connected MCPs

  • πŸ“Š Response Aggregation: Combines responses from multiple MCPs when needed

  • ⚑ Async Execution: Parallel execution for faster responses

  • 🎯 Query Analysis: Understands query intent to route to correct MCPs

  • πŸ”„ Fallback Support: Automatically falls back to rule-based routing if AI fails

Architecture

User Query
    β”‚
    β–Ό
β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚  Master MCP Server  β”‚
β”‚  β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”  β”‚
β”‚  β”‚ Query Analyzerβ”‚  β”‚
β”‚  β””β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”˜  β”‚
β”‚          β”‚          β”‚
β”‚          β–Ό          β”‚
β”‚  β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”  β”‚
β”‚  β”‚ MCP Router    β”‚  β”‚
β”‚  β””β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”˜  β”‚
β”‚          β”‚          β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”Όβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
           β”‚
    β”Œβ”€β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”
    β”‚             β”‚
    β–Ό             β–Ό
β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”  β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚ MCP #1  β”‚  β”‚ MCP #2  β”‚
β”‚ Router  β”‚  β”‚ Coding  β”‚
β””β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”˜  β””β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”˜
     β”‚            β”‚
     β””β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”˜
           β”‚
           β–Ό
    β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
    β”‚ Response β”‚
    β”‚ Aggregatorβ”‚
    β””β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”˜
          β”‚
          β–Ό
    User Response

Installation

cd master-mcp
pip install -r requirements.txt

AI Routing Setup (Optional)

The Master MCP works out-of-the-box without API keys using rule-based routing.

For enhanced AI-powered routing, set an API key:

# Option 1: OpenAI (default)
export OPENAI_API_KEY=your_key_here

# Option 2: Anthropic
export ANTHROPIC_API_KEY=your_key_here
export MASTER_MCP_AI_PROVIDER=anthropic
export MASTER_MCP_AI_MODEL=claude-3-5-haiku

Routing Modes:

Mode

API Key Required

Speed

Intelligence

Rule-based (default)

❌ No

⚑ Fast

Good

AI-powered

βœ… Yes

πŸ”„ +200ms

Excellent

To disable AI routing even if API key is set:

export MASTER_MCP_USE_AI=false

Configuration

Create a config.json file to register MCP servers:

{
  "mcp_servers": {
    "mcp-router": {
      "command": "python3",
      "args": ["/path/to/mcp-router/src/mcp_server.py"],
      "env": {}
    },
    "mcp-coding-agent": {
      "command": "python3",
      "args": ["/path/to/mcp-coding-agent/src/main.py"],
      "env": {}
    }
  }
}

Usage

As MCP Server (Cursor Integration) - Recommended

The Master MCP is now integrated with Cursor! See CURSOR_SETUP.md for detailed instructions.

Quick Start:

  1. The Master MCP has been added to your ~/.cursor/mcp.json

  2. Restart Cursor

  3. Use it:

    @master-mcp query_mcp "What model should I use for debugging?"
    @master-mcp list_mcps

Benefits:

  • 🎯 Auto-discovers all your existing MCPs

  • πŸ€– Intelligent query routing (AI or rule-based)

  • πŸ“Š Aggregates responses from multiple MCPs

  • πŸ”Œ Works out-of-the-box (no API key required for rule-based routing)

Standalone MCP Server

Add to any MCP client's configuration:

{
  "version": "1.0",
  "mcpServers": {
    "master-mcp": {
      "command": "python3",
      "args": ["/path/to/master-mcp/src/master_mcp_server.py"],
      "env": {
        "MASTER_MCP_USE_AI": "true"
      }
    }
  }
}

CLI Usage

python src/master_mcp_server.py --query "What model should I use for debugging?"

How It Works

  1. Query Analysis: Analyzes user query to determine intent

  2. MCP Selection: Selects appropriate MCP(s) based on query

  3. Tool Selection: Chooses the right tool(s) from selected MCPs

  4. Execution: Calls MCP tools (in parallel when possible)

  5. Aggregation: Combines responses into a unified result

  6. Response: Returns formatted response to user

Related MCP Connectors

Related MCP Servers

  • A
    license
    Not graded
    quality
    Not graded
    maintenance
    An MCP server implementation that standardizes how AI applications access tools and context, providing a central hub that manages tool discovery, execution, and context management with a simplified configuration system.
    13
    -
  • F
    license
    Not graded
    quality
    D
    maintenance
    A centralized management platform that aggregates multiple Model Context Protocol (MCP) servers into a single unified endpoint for AI agents. It provides a web interface for hot-swappable tool management, proxying of existing servers, and AI-powered generation of custom MCP plugins.
    1
    -
  • A
    license
    B
    quality
    D
    maintenance
    A configurable MCP server that intelligently routes natural language queries to the appropriate microservice endpoint based on user-defined service configurations.
    8
    1 npm
    MIT