xue20010808_threatnews

xue20010808_threatnews

by xue20010808
An MCP server designed for collecting and analyzing threat information in cybersecurity.

ThreatNews MCP Server: Cybersecurity Threat Information Collection

Overview

The ThreatNews MCP Server is a specialized tool designed for collecting and managing cybersecurity threat information. It leverages the MCP (Modular Command Protocol) framework to streamline the process of gathering threat data, making it an essential resource for cybersecurity professionals.

Key Features

  • Automated Threat Data Collection: Collects threat information based on specified date ranges.
  • Integration with Neo4j: Optionally creates a Neo4j knowledge graph for advanced data visualization and analysis.
  • Customizable Configuration: Supports environment variables and command-line arguments for flexible deployment.

Tools and Components

  • collect.py: The main script for collecting threat data.
  • main.py: Entry point for running the MCP server.
  • pyproject.toml: Configuration file for Python dependencies.
  • smithery.jpg: Example visualization of the tool in action.

Configuration

To set up the ThreatNews MCP Server, configure the mcp.json file with the following structure:

{
  "mcpServers": {
    "Threat_news": {
      "command": "uv",
      "args": ["--directory", "/path/to/mcp_test/threatmcp", "run", "collect.py"],
      "env": {
        "API_KEY": "your_api_key_here"
      }
    },
    "neo4j": {
      "command": "npx",
      "args": ["@alanse/mcp-neo4j-server"],
      "env": {
        "NEO4J_URI": "bolt://localhost:7687",
        "NEO4J_USERNAME": "neo4j",
        "NEO4J_PASSWORD": "your_password_here"
      }
    }
  }
}

Usage

To collect threat information, use the following command structure:

TOOL: collect_threat_info arguments": {
  "start_year": "2024",
  "start_month": "3",
  "start_day": "1",
  "end_year": "2024",
  "end_month": "3",
  "end_day": "10"
}

Visualization in Smithery

ThreatNews Visualization

Resources

Activity

Activity

Languages

  • Python 100.0%

Support

For issues or feature requests, please report here.

Features & Capabilities

Categories
mcp_server model_context_protocol python cybersecurity threat_intelligence neo4j api_integration

Implementation Details

View on GitHub

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Repository Info

xue20010808 Organization

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