leo-claude-mktplace/plugins/data-platform

data-platform Plugin

Data engineering tools with pandas, PostgreSQL/PostGIS, and dbt integration for Claude Code.

Features

• pandas Operations: Load, transform, and export DataFrames with persistent data_ref system
• PostgreSQL/PostGIS: Database queries with connection pooling and spatial data support
• dbt Integration: Build tool wrapper with pre-execution validation

Installation

This plugin is part of the leo-claude-mktplace. Install via:

# From marketplace
claude plugins install leo-claude-mktplace/data-platform

# Setup MCP server venv
cd ~/.claude/plugins/marketplaces/leo-claude-mktplace/mcp-servers/data-platform
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Configuration

PostgreSQL (Optional)

Create ~/.config/claude/postgres.env:

POSTGRES_URL=postgresql://user:password@host:5432/database

dbt (Optional)

Add to project .env:

DBT_PROJECT_DIR=/path/to/dbt/project
DBT_PROFILES_DIR=~/.dbt

Commands

Command	Description
/initial-setup	Interactive setup wizard for PostgreSQL and dbt configuration
/ingest	Load data from files or database
/profile	Generate data profile and statistics
/data-quality	Data quality assessment with pass/warn/fail scoring
/schema	Show database/DataFrame schema
/explain	Explain dbt model lineage
/lineage	Visualize data dependencies (ASCII)
/lineage-viz	Generate Mermaid flowchart for dbt lineage
/run	Execute dbt models
/dbt-test	Run dbt tests with formatted results

Agents

Agent	Description
data-ingestion	Data loading and transformation specialist
data-analysis	Exploration and profiling specialist

data_ref System

All DataFrame operations use a data_ref system for persistence:

# Load returns a reference
read_csv("data.csv") → {"data_ref": "sales_data"}

# Use reference in subsequent operations
filter("sales_data", "amount > 100") → {"data_ref": "sales_data_filtered"}
describe("sales_data_filtered") → {statistics}

Example Workflow

/ingest data/sales.csv
# → Loaded 50,000 rows as "sales_data"

/profile sales_data
# → Statistical summary, null counts, quality assessment

/schema orders
# → Column names, types, constraints

/lineage fct_orders
# → Dependency graph showing upstream/downstream models

/run dim_customers
# → Pre-validates then executes dbt model

Tools Summary

pandas (14 tools)

read_csv, read_parquet, read_json, to_csv, to_parquet, describe, head, tail, filter, select, groupby, join, list_data, drop_data

PostgreSQL (6 tools)

pg_connect, pg_query, pg_execute, pg_tables, pg_columns, pg_schemas

PostGIS (4 tools)

st_tables, st_geometry_type, st_srid, st_extent

dbt (8 tools)

dbt_parse, dbt_run, dbt_test, dbt_build, dbt_compile, dbt_ls, dbt_docs_generate, dbt_lineage

Memory Management

• Default limit: 100,000 rows per DataFrame
• Configure via DATA_PLATFORM_MAX_ROWS environment variable
• Use chunk_size parameter for large files
• Monitor with list_data tool

SessionStart Hook

On session start, the plugin checks PostgreSQL connectivity and displays a warning if unavailable. This is non-blocking - pandas and dbt tools remain available.