mcp_server
MCP（多功能计算平台）服务器是一个功能强大的后端服务，支持文件访问、数据库连接、API集成和向量数据库访问等多种功能。
MCP服务器是一个专为与大型语言模型（如通义千问）集成而设计的后端服务。它提供了文件访问、数据库连接、API集成和向量数据库访问等多种功能。MCP服务器支持完整的Docker部署配置，并提供了通义千问调用示例。项目结构清晰，包含源代码、Docker配置、示例代码和文档等模块。用户可以通过简单的步骤快速启动服务，并使用通义千问客户端进行文件上传、向量存储和相似度搜索等操作。
Features
- {'name': '文件访问', 'description': '支持上传、下载、列表和删除文件操作。'}
- {'name': '数据库连接', 'description': '集成MongoDB，支持文档的增删改查。'}
- {'name': 'API集成', 'description': '支持调用外部API服务。'}
- {'name': '向量数据库', 'description': '支持向量存储和相似度搜索。'}
- {'name': 'Docker部署', 'description': '提供完整的Docker配置，支持一键部署。'}
Usage with Different Platforms
docker
bash
docker-compose -f docker/docker-compose.yml up -d
python
python
from examples.qwen_client import QwenMCPClient
# 初始化客户端
client = QwenMCPClient("http://localhost:8000")
# 上传文件
file_info = client.upload_file("example.txt")
# 存储向量
vector = [0.1, 0.2, 0.3] * 512 # 1536维向量
metadata = {"text": "这是一个示例文本", "source": "通义千问"}
vector_info = client.store_vector("qwen_embeddings", vector, metadata)
# 搜索向量
query_vector = [0.15, 0.25, 0.35] * 512
search_results = client.search_vector("qwen_embeddings", query_vector, top_k=3)
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