EnrichB2B MCP Server
MCP 模板服务器
一个实现模型上下文协议 (MCP) 的模板服务器,集成了 OpenAI、Anthropic 和 EnrichB2B。
设置
创建虚拟环境:
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate安装依赖项:
pip install -r requirements.txt设置环境变量:
cp .env.example .env
# Edit .env with your API keys and configurationRelated MCP server: Prospeo MCP Server
运行服务器
开发模式:
python server.py或者使用 MCP CLI:
mcp dev server.py特征
OpenAI GPT-4 集成
人择克劳德积分
EnrichB2B LinkedIn 数据集成
FastAPI 和 Uvicorn 服务器
环境配置
示例资源和工具
结构化项目布局
项目结构
.
├── .env.example # Template for environment variables
├── .gitignore # Git ignore rules
├── README.md # This file
├── requirements.txt # Python dependencies
├── enrichb2b.py # EnrichB2B API client
└── server.py # MCP server implementation用法
启动服务器
使用任何 MCP 客户端进行连接
使用提供的工具和资源:
config://app获取服务器配置get_profile_details- 获取 LinkedIn 个人资料信息get_contact_activities- 获取 LinkedIn 用户最近的活动和帖子gpt4_completion- 使用 GPT-4 生成文本claude_completion- 使用 Claude 生成文本analysis_prompt- 文本分析模板
EnrichB2B 工具
获取个人资料详情
获取有关 LinkedIn 个人资料的详细信息:
result = await get_profile_details(
linkedin_url="https://www.linkedin.com/in/username",
include_company_details=True,
include_followers_count=True
)获取联系人活动
从 LinkedIn 个人资料中获取最近的活动和帖子:
result = await get_contact_activities(
linkedin_url="https://www.linkedin.com/in/username",
pages=1, # Number of pages (1-50)
comments_per_post=1, # Comments per post (0-50)
likes_per_post=None # Likes per post (0-50)
)发展
要添加新功能:
使用
@mcp.tool()装饰器添加新工具使用
@mcp.resource()装饰器添加新资源使用
@mcp.prompt()装饰器添加新提示
执照
麻省理工学院
This server cannot be deployed
Maintenance
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