aie-mcp

Name: aie-mcp
Availability: InStock
Author: AI Engineer

This project hosts the AI Engineer Conference 2025 talk submission system and MCP server. Built using Cloudflare, it is designed for developers to easily test and run locally.

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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

+1 more

Installation

Prerequisites

Please specify required software and versions:

Node.js: 18.0.0 or higher

npm: 8.0.0 or higher

Claude Desktop: Latest version

Installation Steps

1. Clone Repository

bash
git clone git@github.com:aiDotEngineer/aie-mcp.git
cd aie-mcp

2. Install Dependencies

bash
npm install

3. Start Server

bash
npx wrangler dev

4. Verify in Browser

Access http://localhost:8787/ to confirm that the server is running correctly.

Troubleshooting

Common Issues

Issue: Server won't start Solution: Check Node.js version and reinstall dependencies. Issue: Not recognized by Claude Desktop Solution: Verify configuration file path and syntax.

Configuration

Basic Configuration

Claude Desktop Setup

Edit ~/.config/claude-desktop/claude_desktop_config.json (macOS/Linux) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

json
{
  "mcpServers": {
    "AIECONF": {
      "url": "https://ai-engineer-wf-2025.swyx-5de.workers.dev/sse"
    }
  }
}

Advanced Configuration

Security Settings

Store API keys in environment variables or secure configuration files

Set appropriate file access permissions

Adjust logging levels

Performance Tuning

Configure timeout values

Limit concurrent executions

Set up caching

Configuration Example

Basic Configuration

json
{
  "mcpServers": {
    "example-mcp": {
      "command": "node",
      "args": ["server.js"],
      "env": {
        "PORT": "3000",
        "LOG_LEVEL": "info"
      }
    }
  }
}

Examples

Basic Usage

Here are basic usage examples for the MCP server:

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);

Advanced Examples

Automation Script

bash
#!/bin/bash
Batch processing example

for file in *.txt; do
  mcp-tool process "$file"
done

API Integration

python
Python example
import requests
import json

def call_mcp_tool(tool_name, params):
    response = requests.post(
        'http://localhost:3000/mcp/call',
        json={
            'tool': tool_name,
            'parameters': params
        }
    )
    return response.json()

Usage example
result = call_mcp_tool('analyze', {
    'input': 'sample data',
    'options': {'format': 'json'}
})