- local_pgsql
local_pgsql
Overview
MCP (Modular Control Platform) - Overview
Introduction
The Modular Control Platform (MCP) is an extensible Python framework designed to automate and streamline database analytics workflows. It provides a standardized interface for data exploration, statistical analysis, and custom query execution through a plugin-based architecture.
Core Features
Database Operations
- Schema Inspection
- Table listing and metadata retrieval
- Column-level schema analysis
- Data Access
- Row sampling with configurable limits
- Parameterized custom query execution
Analytical Capabilities
- Descriptive Statistics
- Central tendency measures (mean, median)
- Dispersion metrics (std. deviation, variance)
- Relationship Analysis
- Correlation matrix generation
- Cross-column dependency detection
- Advanced Analytics
- Time series aggregation (daily/weekly/monthly)
- Anomaly detection (Z-score, IQR methods)
Automation Tools
- Predefined Analysis Templates
- Common analytical workflows
- SQL query patterns
- Dynamic Tool Registration
- Plugin-style function integration
- Type-annotated interface contracts
Technical Architecture
@mcp.tool("example_tool")
def tool_function(params: Dict) -> List[Dict]:
"""Type-safe tool definition"""
return processed_data
Server Config
{
"mcpServers": {
"github": {
"command": "docker",
"args": [
"build",
"-t",
"mcp-pgsql-python-service",
".",
"&&",
"docker",
"run",
"-p",
"8000:8000",
"-e",
"DB_HOST=${DB_HOST}",
"-e",
"DB_PORT=${DB_PORT:-5432}",
"-e",
"DB_NAME=${DB_NAME}",
"-e",
"DB_USER=${DB_USER}",
"-e",
"DB_PASSWORD=${DB_PASSWORD}",
"mcp-pgsql-python-service"
],
"env": {
"GITHUB_PERSONAL_ACCESS_TOKEN": "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",
"DB_HOST": "postgres",
"DB_PORT": "5432",
"DB_NAME": "postgres",
"DB_USER": "postgres",
"DB_PASSWORD": "postgres"
}
}
}
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