Legion_mcp: AI Chaos Orchestration | Military-Grade Compute Power

Key Features of Legion_mcp: AI Chaos Orchestration | Military-Grade Compute Power?

• Military-Grade Compute Engine: Processes thousands of concurrent SQL queries with zero latency, even under chaotic workloads.
• AI-Powered Query Optimization: Automatically refines SQL statements using machine learning models trained on battle-tested datasets.
• Context-Aware Orchestration: Maintains seamless continuity across distributed database clusters, ensuring operations flow like a synchronized strike force.
• Flexible Deployment: Operates in Kubernetes clusters, bare-metal servers, or even Raspberry Pi deployments (tested in extreme conditions).

Use Cases of Legion_mcp: AI Chaos Orchestration | Military-Grade Compute Power?

This isn't just another database tool—it’s a strategic asset for:

Legion MCP (Model Context Protocol) Server

A server that helps people access and query data in databases using the Legion Query Runner with integration of the Model Context Protocol (MCP) Python SDK.

Features

• Database access via Legion Query Runner
• Model Context Protocol (MCP) support for AI assistants
• Expose database operations as MCP resources, tools, and prompts
• Multiple deployment options (standalone MCP server, FastAPI integration)
• Query execution and result handling
• Flexible configuration via environment variables, command-line arguments, or MCP settings JSON

What is MCP?

The Model Context Protocol (MCP) is a specification for maintaining context in AI applications. This server uses the MCP Python SDK to:

• Expose database operations as tools for AI assistants
• Provide database schemas and metadata as resources
• Generate useful prompts for database operations
• Enable stateful interactions with databases

Setup with uv

This project uses uv for dependency management.

Installation

1. Install uv:

pip install uv

2. Create and activate a virtual environment:

uv venv
source .venv/bin/activate  # On Unix/macOS
# OR
.venv\Scripts\activate  # On Windows

3. Install dependencies:

uv pip install -e .

Development

To run the server in development mode:

mcp dev mcp_server.py

For production mode:

python mcp_server.py

Testing

Run tests with:

uv pip install -e ".[dev]"
pytest

Standalone FastMCP Server

The simplest approach using the high-level FastMCP API:

python mcp_server.py

This runs a standalone MCP server using the FastMCP class, which provides:

• Easy setup with decorators for resources, tools, and prompts
• Automatic context management
• Lifecycle management via lifespan

MCP Development

For development with the MCP Inspector tool:

mcp dev mcp_server.py

MCP Configuration

Environment Variables

When running with the MCP CLI, you can configure the database connection using environment variables:

export DB_TYPE="pg"  # or mysql, postgresql, etc.
export DB_CONFIG='{"host":"localhost","port":5432,"user":"username","password":"password","dbname":"database_name"}'
mcp dev mcp_server.py

Command Line Arguments

For direct execution, use command line arguments:

python mcp_server.py --db-type pg --db-config '{"host":"localhost","port":5432,"user":"username","password":"password","dbname":"database_name"}'

MCP Settings JSON

To integrate with AI assistants like Claude, you can configure the MCP server in the settings JSON:

{
  "legion_mcp": {
    "command": "uv",
    "args": [
      "--directory",
      "/path/to/legion-mcp",
      "run",
      "mcp_server.py"
    ],
    "env": {
      "DB_TYPE": "pg",
      "DB_CONFIG": "{\"host\":\"localhost\",\"port\":5432,\"user\":\"username\",\"password\":\"password\",\"dbname\":\"database_name\"}"
    },
    "disabled": false,
    "autoApprove": []
  }
}

This configuration:

• Specifies the command to run the server (uv run mcp_server.py)
• Sets the working directory (/path/to/legion-mcp)
• Provides database connection details via environment variables
• Controls whether the MCP is enabled or disabled
• Can specify actions to auto-approve without user confirmation

Place this configuration in your editor's MCP settings file to enable database access for your AI assistant.

Exposed MCP Capabilities

Resources

• schema://all - Get the complete database schema

Tools

• execute_query - Execute a SQL query and return results as a markdown table
• execute_query_json - Execute a SQL query and return results as JSON
• get_table_columns - Get column names for a specific table
• get_table_types - Get column types for a specific table
• get_query_history - Get the recent query history

Prompts

• sql_query - Create an SQL query against the database
• explain_query - Explain what a SQL query does
• optimize_query - Optimize a SQL query for better performance

Development

Run tests:

pytest

License

This repository is licensed under CC BY-NC-SA 4.0