MCP Installer测评：一键管理AI智能体的工具库

# 检查当前Node.js版本
node -v
npx -v

# 检查Python版本
python --version

# 使用nvm-windows管理多个Node版本
nvm install 22.14.0
nvm use 22.14.0

node -v  # 显示Node.js版本
npx -v   # 显示npx版本

{
  "mcpServers": {
    "mcp-easy-installer": {
      "command": "node",
      "args": [
        "path-to\\mcp-easy-installer\\build\\index.js"
      ],
      "env": {
        "GITHUB_TOKEN": "your_github_token"
      }
    }
  }
}

# 更新Homebrew并安装Node.js
brew update
brew install node

echo "Node.js version: $(node -v)"
echo "npm version: $(npm -v)" 
echo "npx version: $(npx -v)"

echo 'export PATH="/usr/local/opt/node@16/bin:$PATH"' >> ~/.zshrc

{
  "mcpServers": {
    "mcp-easy-installer": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-easy-installer"
      ]
    }
  }
}

# Ubuntu/Debian
sudo apt update
sudo apt install nodejs npm

# CentOS/RHEL  
sudo yum install nodejs npm

# 安装nvm
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.0/install.sh | bash

# 安装并使用Node.js
nvm install 18
nvm use 18

node -v
npm -v
npx -v

{
  "mcpServers": {
    "mcp-easy-installer": {
      "command": "npx",
      "args": ["-y", "mcp-easy-installer"]
    },
    "filesystem": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-filesystem",
        "/Users/username/Desktop",
        "/path/to/other/allowed/dir"
      ]
    }
  }
}

# 使用MCP Installer搜索并安装学术相关工具
# 安装arXiv搜索工具
mcp-installer install arxiv-search-tool

# 安装文件系统工具
mcp-installer install filesystem-server

# 安装网络搜索工具
mcp-installer install web-search-tool

import asyncio
from mcp.server import Server
from mcp.server.stdio import stdio_server
import aiohttp
from mcp.server.models import ToolResult
from mcp.types import Tool

# 创建Server实例
app = Server("academic-assistant")

@app.tool()
async def search_arxiv(query: str, max_results: int = 5) -> Tool:
    """在arXiv库中搜索科学论文。

    Args:
        query: 搜索关键词，例如：'large language model'。
        max_results: 返回的最大结果数量，默认为5。
    """
    base_url = "http://export.arxiv.org/api/query"
    params = {
        "search_query": f"all:{query}",
        "start": 0,
        "max_results": max_results,
        "sortBy": "submittedDate",
        "sortOrder": "descending"
    }

    try:
        async with aiohttp.ClientSession() as session:
            async with asyncio.timeout(15):
                async with session.get(base_url, params=params) as response:
                    response.raise_for_status()
                    data = await response.text()

        # 简化处理：实际应用中应解析XML
        if len(data) > 500:
            preview = data[:500] + "..."
        else:
            preview = data

        result_content = f"**arXiv Search Results for '{query}':**\n\nRaw API response preview:\n{preview}"

        return ToolResult(content=result_content)

    except asyncio.TimeoutError:
        return ToolResult(content="arXiv search request timed out after 15 seconds.", isError=True)
    except Exception as e:
        return ToolResult(content=f"An unexpected error occurred: {str(e)}", isError=True)

@app.tool()
async def save_research_notes(topic: str, notes: str, file_path: str) -> Tool:
    """保存研究笔记到文件系统。

    Args:
        topic: 研究主题。
        notes: 研究笔记内容。
        file_path: 保存文件的路径。
    """
    try:
        import os
        import datetime
        
        # 确保目录存在
        os.makedirs(os.path.dirname(file_path), exist_ok=True)
        
        # 添加时间戳
        timestamp = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
        formatted_notes = f"# {topic}\n\n时间: {timestamp}\n\n{notes}"
        
        # 写入文件
        with open(file_path, 'w', encoding='utf-8') as f:
            f.write(formatted_notes)
            
        return ToolResult(content=f"研究笔记已成功保存到: {file_path}")
        
    except Exception as e:
        return ToolResult(content=f"保存文件时出错: {str(e)}", isError=True)

async def main():
    async with stdio_server() as (read_stream, write_stream):
        await app.run(
            read_stream,
            write_stream,
            app.create_initialization_options()
        )

if __name__ == "__main__":
    asyncio.run(main())

{
  "mcpServers": {
    "academic-assistant": {
      "command": "python",
      "args": ["/path/to/academic_assistant.py"]
    },
    "mcp-easy-installer": {
      "command": "npx",
      "args": ["-y", "mcp-easy-installer"]
    }
  }
}

# 通过自然语言指令使用助手
"请搜索关于大语言模型的最新论文，并将重要观点保存到研究笔记中"