MCP AI SOC Sher

What is MCP AI SOC Sher?

MCP AI SOC Sher is an AI-driven Security Operations Center (SOC) Text2SQL framework based on the Model Context Protocol (MCP). It converts natural language prompts into optimized SQL queries while integrating built-in security threat analysis and monitoring. It is intended for security analysts, developers, and SOC teams who need to query databases using plain English and assess the security of the resulting SQL.

How to use MCP AI SOC Sher?

Install via pip install mcp-ai-soc-sher, set the OPENAI_API_KEY environment variable (or configure it in a .env file), then run the server from the command line using mcp-ai-soc --type local --stdio (for STDIO) or --sse (for SSE) or --type remote (for REST API). You can also use the Python API by importing LocalMCPServer from mcp_ai_soc_sher.local. Send queries via HTTP POST to /api/sql with an X-API-Key header for the REST interface.

Key features of MCP AI SOC Sher

• Convert natural language to optimized SQL queries
• Support STDIO, SSE, and REST API interfaces
• Built-in rule-based and AI-powered security threat analysis
• Connect to SQLite or Snowflake databases
• Real-time streaming query processing feedback
• Security Operations Center monitoring capabilities

Use cases of MCP AI SOC Sher

• Security analysts querying databases for suspicious activities in natural language
• Automating threat hunting by converting incident descriptions to SQL
• Monitoring sensitive table access with integrated security checks
• Enabling non-technical SOC staff to run ad‑hoc database queries safely
• Building custom security dashboards that require dynamic SQL generation