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AI_SOC_MCP_Server_Sher

README.md2.54 kB
# MCP AI SOC Sher A powerful AI-driven Security Operations Center (SOC) Text2SQL framework based MCP Server (Local and Remote) for converting natural language Prompts to SQL queries dynamically, with integrated security threat analysis and monitoring. ## Features - **Text2SQL Conversion**: Convert natural language queries to optimized SQL - **Multiple Interfaces**: Support for STDIO, SSE, and REST API - **Security Threat Analysis**: Built-in SQL query security analysis - **Multiple Database Support**: Connect to SQLite or Snowflake databases - **Streaming Responses**: Real-time query processing feedback - **SOC Monitoring**: Security Operations Center monitoring capabilities ## Installation ```bash pip install mcp-ai-soc-sher ``` ## Quick Start ```python # Set your OpenAI API key import os os.environ["OPENAI_API_KEY"] = "your-api-key-here" # Use as local server from mcp_ai_soc_sher.local import LocalMCPServer server = LocalMCPServer() server.start() # Or run from command line # mcp-ai-soc --type local --stdio --sse ``` ## Command Line Usage ```bash # Run local server with STDIO interface mcp-ai-soc --type local --stdio # Run local server with SSE interface mcp-ai-soc --type local --sse # Run remote server with REST API mcp-ai-soc --type remote ``` ## Configuration Create a `.env` file with your configuration: ``` OPENAI_API_KEY=your_openai_api_key_here MCP_DB_URI=sqlite:///your_database.db MCP_SECURITY_ENABLE_THREAT_ANALYSIS=true ``` See the [documentation](docs/configuration.md) for all configuration options. ## Example ```python import json import requests # Query the server response = requests.post( "http://localhost:8000/api/sql", headers={"Content-Type": "application/json", "X-API-Key": "your-api-key"}, json={ "query": "Find all suspicious login attempts in the last 24 hours", "optimize": True, "execute": True } ) # Process the response result = response.json() print(f"SQL Query: {result['sql']}") if result['results']: print("Results:") for row in result['results']: print(row) ``` ## Security Features - Rule-based and AI-powered SQL query security analysis - Detection of potential SQL injection attacks - Sensitive table access monitoring - Configurable security levels and actions ## License MIT License with Additional Conditions. Copyright (c) 2025 Akram Sheriff. See [LICENSE](LICENSE) for details. ## Contributing Contributions are welcome! Please see [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.

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