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EnrichB2B MCP Server

by moonlabsai
GitHub
Python
  • Linux
OverviewInspectNewSchemaRelated ServersReviewsScore
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Integrations

  • Manages environment configuration for API keys and server settings.

  • Powers the underlying server architecture for the MCP implementation.

  • Supports version control with provided .gitignore rules for the project.

MCP Template Server

A template server implementing the Model Context Protocol (MCP) with OpenAI, Anthropic, and EnrichB2B integration.

Setup

  1. Create a virtual environment:
python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate
  1. Install dependencies:
pip install -r requirements.txt
  1. Set up environment variables:
cp .env.example .env # Edit .env with your API keys and configuration

Running the Server

Development mode:

python server.py

Or using MCP CLI:

mcp dev server.py

Features

  • OpenAI GPT-4 integration
  • Anthropic Claude integration
  • EnrichB2B LinkedIn data integration
  • FastAPI and Uvicorn server
  • Environment configuration
  • Example resources and tools
  • Structured project layout

Project Structure

. ├── .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

Usage

  1. Start the server
  2. Connect using any MCP client
  3. Use the provided tools and resources:
    • config://app - Get server configuration
    • get_profile_details - Get LinkedIn profile information
    • get_contact_activities - Get LinkedIn user's recent activities and posts
    • gpt4_completion - Generate text using GPT-4
    • claude_completion - Generate text using Claude
    • analysis_prompt - Template for text analysis

EnrichB2B Tools

get_profile_details

Get detailed information about a LinkedIn profile:

result = await get_profile_details( linkedin_url="https://www.linkedin.com/in/username", include_company_details=True, include_followers_count=True )
get_contact_activities

Get recent activities and posts from a LinkedIn profile:

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) )

Development

To add new features:

  1. Add new tools using the @mcp.tool() decorator
  2. Add new resources using the @mcp.resource() decorator
  3. Add new prompts using the @mcp.prompt() decorator

License

MIT

This server cannot be installed

-
security - not tested
F
license - not found
-
quality - not tested

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

A server implementing the Model Context Protocol that enables users to retrieve LinkedIn profile information and activity data via EnrichB2B API, and generate text using OpenAI GPT-4 or Anthropic Claude models.

  1. Setup
    1. Running the Server
      1. Features
        1. Project Structure
          1. Usage
            1. EnrichB2B Tools
          2. Development
            1. License

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