MCP-Gateway
MCP-Gateway
README
MCP Gateway
English | 简体中文
License
This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for more details.
Project Overview
MCP Gateway is an application built with Python. It acts as a central gateway that connects to and aggregates capabilities from multiple backend MCP servers (whether they communicate via Stdio or SSE protocols). Ultimately, it exposes these aggregated capabilities to upstream MCP clients through a unified SSE endpoint (/sse).
Core Advantages:
- Simplified Client Configuration: MCP clients only need to connect to the single address of the MCP Gateway to access the functionalities of all backend services, eliminating the need to configure each backend server individually.
- Capability Aggregation & Orchestration: Aggregates MCP tools with diverse capabilities from various sources, providing a foundation for building more powerful, customized agents focused on specific task domains.
Project File Structure
.
├── config.json # Core configuration file: Defines the backend MCP servers to connect to and manage.
├── main.py # Program entry point: Parses command-line arguments, sets up logging, and starts the web server.
├── bridge_app.py # Starlette application core: Handles forwarding of MCP requests and SSE connection management.
├── client_manager.py # Client manager: Responsible for establishing and maintaining connection sessions with backend MCP servers.
├── capability_registry.py # Capability registry: Dynamically discovers, registers, and manages capabilities provided by all backend MCP servers.
├── config_loader.py # Configuration loader: Responsible for loading and strictly validating the format and content of the `config.json` file.
├── errors.py # Custom exceptions: Defines project-specific error types, such as configuration errors and backend server errors.
├── rich_handler.py # Rich logging handler: Provides beautified, structured console log output.
├── servers/ # Contains built-in/example backend MCP server scripts.
│ ├── bash_server.py # <-- Built-in Bash command execution tool (Linux/macOS/WSL)
│ ├── cmd_server.py # <-- Built-in Windows CMD command execution tool (Windows Only)
│ ├── powershell_server.py # <-- Built-in Windows PowerShell command execution tool (Windows Only)
│ └── wmi_server.py # <-- Built-in Windows WMI query tool (Windows Only)
└── logs/ # Log directory: Stores runtime log files (created automatically).
Built-in MCP Servers
This project comes with four backend MCP Server tools that can be used directly and enabled in config.json without additional configuration:
- Bash Command Execution Tool (
bash_server.py): Executes Bash commands in Linux, macOS, or WSL environments. - Windows CMD Command Execution Tool (
cmd_server.py): Executes CMD commands in Windows environments. - Windows PowerShell Command Execution Tool (
powershell_server.py): Executes PowerShell commands in Windows environments. - Windows WMI Query Tool (
wmi_server.py): Executes WMI queries in Windows environments.
If you encounter the following error in a Linux environment:
error: Distribution `pywin32==310 @ registry+https://pypi.org/simple` can't be installed because it doesn't have a source distribution or wheel for the current platform>Please uninstall the
wmimodule:uv remove wmi
Installation and Setup
This project is written in Python. Using uv for environment and dependency management is recommended.
-
Clone Repository
git clone https://github.com/trtyr/MCP-Gateway.git cd MCP-Gateway -
Create and Activate Virtual Environment
# Create virtual environment uv venv # Activate virtual environment # Linux/macOS source .venv/bin/activate # Windows (Command Prompt/PowerShell) .venv\Scripts\activate -
Install Dependencies
# Install all required dependencies based on pyproject.toml uv sync
After completing these steps, the project is ready to run.
Quick Start
Get Project Help
You can use the -h or --help argument to view all available startup options:
# Windows
uv run python .\main.py -h
# Linux/macOS
uv run python ./main.py -h
The output will be similar to this:
usage: main.py [-h] [--host HOST] [--port PORT] [--log-level {debug,info,warning,error,critical}]
Start MCP_Bridge_Server v3.0.0
options:
-h, --help show this help message and exit
--host HOST Host address (default: 0.0.0.0)
--port PORT Port (default: 9000)
--log-level {debug,info,warning,error,critical}
Set file logging level (default: info)
Start the Project
Use uv run python main.py to start the server. You can specify the host, port, and log-level:
# Listen on all network interfaces on port 9000, set log level to debug
uv run python .\main.py --host 0.0.0.0 --port 9000 --log-level debug
After starting, you will see a Rich beautified console output similar to the image below, showing the server status, connection information, and loaded tools:

MCP Client Connection
After starting MCP Gateway, you can use any MCP-compatible client (such as Cline, Cursor, Claude Desktop, or a custom client) to connect to the SSE endpoint provided by the Gateway.
The default address is http://<Server_IP_Address>:9000/sse (if using the default port).
Example (Using ChatWise Connect):
- Select
SSEconnection type. - Enter the Gateway's SSE URL (e.g.,
http://127.0.0.1:9000/sse). - Click
Connect.

After a successful connection, you can see all backend MCP tools aggregated through the Gateway in the client:

Logs
Runtime logs are automatically saved in the logs folder in the project root directory. Log filenames include timestamps and log levels, making it easy to trace issues.
logs/
├── log_20240801_103000_INFO.log
└── log_20240801_110000_DEBUG.log
...

Configuration File (config.json)
The core configuration file config.json is located in the project root directory. It defines the backend MCP servers that MCP Gateway needs to connect to and manage.
Each entry represents a backend server. The key is the unique name you assign to that backend server (this name will be used as the prefix for its capabilities), and the value is an object containing the server's configuration.
Two types of backend server connections are supported:
stdio: Communicates with a locally started MCP server process via standard input/output (stdin/stdout).sse: Communicates with a remote or locally running MCP server via the Server-Sent Events (SSE) protocol.
Stdio Type Configuration
Suitable for local MCP server processes whose lifecycle needs to be managed by the Gateway.
Configuration Fields:
type(required): Must be"stdio".command(required): The executable command used to start the server process (e.g.,python,uv,node, or the absolute path to a script/executable).args(required): A list of arguments (List of strings) passed to thecommand.env(optional): A dictionary of environment variables (Dict[str, str]) to set for the child process. If omitted, the child process inherits the Gateway's environment.
Example:
{
"powershell": {
"type": "stdio",
"command": "python",
"args": ["servers/powershell_server.py"]
},
"my_custom_tool": {
"type": "stdio",
"command": "/path/to/my/custom_mcp_server",
"args": ["--port", "ignored_for_stdio", "--some-flag"],
"env": {
"API_KEY": "your_secret_key"
}
}
}
How it Works: When MCP Gateway starts, it uses the specified command and args (along with optional env) to launch a child process. The Gateway communicates with the backend MCP server through this child process's standard input and output. When the Gateway shuts down, it attempts to terminate these child processes.
SSE Type Configuration
Suitable for connecting to already running MCP servers (local or remote), or cases where the Gateway needs to start a local SSE server process before connecting.
Configuration Fields:
type(required): Must be"sse".url(required): The SSE endpoint URL of the backend MCP server (full HTTP/HTTPS address).command(optional): If specified, the Gateway will run this command at startup to launch the local SSE server.args(optional, only whencommandis specified): A list of arguments passed to thecommand.env(optional, only whencommandis specified): Environment variables to set for the locally launched child process.
Example 1: Connecting to an already running remote SSE server
{
"remote_search_service": {
"type": "sse",
"url": "https://mcp.example.com/search/sse"
}
}
Example 2: Gateway starts a local SSE server and connects
{
"local_sse_server": {
"type": "sse",
"url": "http://127.0.0.1:8080/sse",
"command": "uv",
"args": ["run", "python", "servers/my_local_sse_app.py", "--port", "8080"],
"env": { "MODE": "production" }
}
}
How it Works:
- Only
urlprovided: The Gateway directly attempts to connect to the specifiedurl. url,command,argsprovided: The Gateway first usescommandandargsto start a local process (expecting this process to listen on the address and port corresponding tourl). It then waits for a short period (LOCAL_SSE_STARTUP_DELAYdefined inclient_manager.py) before attempting to connect to theurl. When the Gateway shuts down, it attempts to terminate this local process.
Configuration Addition Examples
Here are examples of how to add third-party MCP servers to config.json.
Stdio Example: Playwright MCP
Suppose you want to integrate Playwright's MCP server (@playwright/mcp).
-
Understand Startup Method: Playwright MCP is typically started using
npx @playwright/mcp@latest. This is a Node.js package executed vianpx. -
Configure
config.json:{ // ... other server configurations ... "playwright": { "type": "stdio", "command": "npx", "args": ["@playwright/mcp@latest"] } // ... other server configurations ... }Here,
commandisnpx, andargscontains the Playwright MCP package name and version. -
Restart Gateway: Save
config.jsonand restart MCP Gateway.
After starting, you should see tools named playwright/... (e.g., playwright/browse) in the console logs and your client.



SSE Example: ENScan_GO (Local Start)
Suppose you want to integrate ENScan_GO, a Go program that can be started with ./enscan --mcp and provides an SSE service at http://localhost:8080.
-
Get Executable File: Download the ENScan_GO executable (e.g.,
enscan-v1.2.1-windows-amd64.exe) and place it in an accessible location (e.g., theservers/directory or in your system PATH). -
Configure
config.json:{ // ... other server configurations ... "enscan": { "type": "sse", "url": "http://127.0.0.1:8080/sse", // Address ENScan_GO listens on // Note: Ensure path separators are correct on Windows, or use an absolute path "command": "servers/enscan-v1.2.1-windows-amd64.exe", // Path to the executable "args": ["--mcp"] // Startup arguments } // ... other server configurations ... }Here, we specify
typeassse, provide theurlit listens on, and usecommandandargsto tell the Gateway how to start this local SSE server. -
Restart Gateway: Save
config.jsonand restart MCP Gateway.
The Gateway will first start the ENScan_GO process, then connect to http://127.0.0.1:8080/sse. After starting, you should see tools named enscan/....

Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.