Which integrations are available for this server?

Provides tools to interact with SQLite databases, including querying, listing tables, and schema inspection.

How do I use MCP Multi-Server Gateway?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP Multi-Server Gateway list all registered servers" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

MCP Multi-Server Gateway

by moaaz01

Overview Schema Source Related Servers Discussions Admin

Python

Hybrid

🌐 MCP Multi-Server Gateway

Aggregate, route, and orchestrate multiple MCP backend servers behind a single MCP endpoint. Connect one gateway to Claude Desktop/Cursor and access all your MCP servers — weather, database, file system, and more.

License: MIT Python 3.10+

✨ Why a Gateway?

Instead of configuring each MCP server individually in your client:

// ❌ Without Gateway: 3 entries in claude_desktop_config.json
{
  "weather": { "command": "...", "args": ["weather_server.py"] },
  "sqlite": { "command": "...", "args": ["sqlite_server.py", "--db-path", "..."] },
  "filesystem": { "command": "...", "args": ["filesystem_server.py", "--sandbox", "..."] }
}

// ✅ With Gateway: 1 entry — register/unregister servers at runtime
{
  "gateway": { "command": "python", "args": ["gateway.py"] }
}

Related MCP server: mcpware

✨ Features

🔧 5 Tools: register_server, remove_server, list_servers, call_backend, route_pipeline
⏱️ Async Routing: Concurrent tool execution across backends via asyncio
📋 Pipeline Support: Pre-configured multi-step workflows (weather-analysis, database-report)
📝 Auto-Registration: Load backend config from JSON file on startup
🔌 Runtime Dynamic: Register/unregister servers without restarting
⏲️ Timeout Handling: 10-second per-backend timeout prevents hangs
🖥️ Dual Transport: stdio and Streamable HTTP

🚀 Quick Start

# 1. Setup
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

# 2. Start the gateway
python gateway.py

# 3. Register backend servers (from MCP client)
register_server(name="weather", command="python", args="weather_server.py", description="Weather alerts")
register_server(name="sqlite", command="python", args="sqlite_server.py --db-path /tmp/sample.db", description="Database queries")

With auto-registration:

python gateway.py --auto-register gateway-config.json

🛠️ Tools Reference

`register_server(name, command, args, description) -> str`

`remove_server(name) -> str`

Remove a registered server.

`list_servers() -> str`

List all registered backends with status and tool counts.

`call_backend(server, tool, params) -> str`

Execute a tool on a specific backend. params is a JSON string.

`route_pipeline(scenario) -> str`

Execute a pre-configured multi-step pipeline:

"weather-analysis" — alerts + forecast
"database-report" — schema inspection + query
"custom" — compose your own workflow

🔌 Connecting to Clients

Claude Desktop

{
  "mcpServers": {
    "gateway": {
      "command": "python",
      "args": ["/ABSOLUTE/PATH/mcp-multi-server-gateway/gateway.py"]
    }
  }
}

Streamable HTTP Mode

python gateway.py --transport streamable-http --port 8003

📁 Project Structure

mcp-multi-server-gateway/
├── gateway.py              # Main gateway server (FastMCP + asyncio)
├── gateway-config.json     # Example auto-registration config
├── requirements.txt
├── setup.sh
├── README.md
└── .gitignore

🏗️ Architecture

         ┌─────────────────────────────────────┐
         │       MCP Client (Claude, etc)       │
         └──────────────┬──────────────────────┘
                        │  single MCP connection
         ┌──────────────▼──────────────────────┐
         │     MCP Multi-Server Gateway         │
         │     (gateway.py on :8003)            │
         │                                      │
         │  register / call_backend / pipeline  │
         └──┬──────────┬──────────┬───────────┘
            │          │          │
     ┌──────▼──┐ ┌─────▼────┐ ┌──▼────────┐
     │ Weather  │ │  SQLite  │ │ FileSystem│
     │ Server   │ │  Server  │ │  Server   │
     └─────────┘ └──────────┘ └───────────┘

💡 Use Cases

Scenario	Tools Involved	Example
DevOps Debugging	sqlite.query + filesystem.read_file	"Check DB schema, then read config file"
Data Analysis	sqlite.list_tables + sqlite.query	"What tables exist? Give me top 10 customers"
Multi-weather check	weather.get_alerts × 2	"Alerts for CA and TX simultaneously"
Automated report	All servers in sequence	"Get weather data → query DB → write report"

📜 License

MIT

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

ActivityInactive

ResponsivenessNo issues

Resources

GitHub Repository

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