mcp_server_exe

Name: mcp_server_exe
Availability: InStock
Author: shadow

mcp_server_exe is a powerful executable server designed to run MCP (Model Context Protocol) services. This tool supports managing multiple MCP services simultaneously, allows for tool chain execution, and features a pluggable system for custom tools. It can integrate with other MCP services via WebSocket connections and offers flexible deployment options, enabling developers to address various automation scenarios.

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Installation

Difficulty

Intermediate

Estimated Time

10-20 minutes

Requirements

Node.js: 18.0.0以上

npm: 8.0.0以上

Installation

Prerequisites

Please specify required software and versions:

Node.js: 18.0.0 or higher

npm: 8.0.0 or higher

Installation Steps

1. Clone Repository

bash
git clone https://github.com/shadowcz007/mcp_server_exe
cd mcp_server_exe

2. Install Dependencies

bash
npm install

3. Start Server

bash
npm start

Troubleshooting

Common Issues

Issue: Server won't start Solution: Check Node.js version and reinstall dependencies.

Configuration

Basic Configuration

MCP Configuration File

Create a configuration file like mcp-sse.json:

json
{
    "mcpServers": {
        "Model Server sse": {
            "url": "http://127.0.0.1:3000"
        },
        "Model Server - stdio": {
            "command": "xxxxx",
            "args": [
                "--transport",
                "stdio"
            ]
        }
    },
    "serverInfo": {
        "serverName": "ws-client-mcp-server",
        "version": "1.0.0",
        "description": "WebSocket client MCP server instance",
        "author": "shadow"
    }
}

Security Settings

Store API keys in secure configuration files

Set appropriate file access permissions

Examples

Basic Usage

Here are basic usage examples for the MCP server:

Using WebSocket Connection

bash
./mcp_server.exe --ws wss://api.xiaozhi.me/mcp/?token=...xxx --mcp-config ./examples/mcp-sse.json

Programmatic Usage

javascript
// JavaScript example (Node.js)
const { MCPClient } = require('@modelcontextprotocol/client');

const client = new MCPClient();
await client.connect();

// Execute tool
const result = await client.callTool('toolName', {
  parameter1: 'value1',
  parameter2: 'value2'
});

console.log(result);