Add new data-platform plugin for data engineering workflows with: MCP Server (32 tools): - pandas operations (14 tools): read_csv, read_parquet, read_json, to_csv, to_parquet, describe, head, tail, filter, select, groupby, join, list_data, drop_data - PostgreSQL/PostGIS (10 tools): pg_connect, pg_query, pg_execute, pg_tables, pg_columns, pg_schemas, st_tables, st_geometry_type, st_srid, st_extent - dbt integration (8 tools): dbt_parse, dbt_run, dbt_test, dbt_build, dbt_compile, dbt_ls, dbt_docs_generate, dbt_lineage Plugin Features: - Arrow IPC data_ref system for DataFrame persistence across tool calls - Pre-execution validation for dbt with `dbt parse` - SessionStart hook for PostgreSQL connectivity check (non-blocking) - Hybrid configuration (system ~/.config/claude/postgres.env + project .env) - Memory management with 100k row limit and chunking support Commands: /initial-setup, /ingest, /profile, /schema, /explain, /lineage, /run Agents: data-ingestion, data-analysis Test suite: 71 tests covering config, data store, pandas, postgres, dbt tools Addresses data workflow issues from personal-portfolio project: - Lost data after multiple interactions (solved by Arrow IPC data_ref) - dbt 1.9+ syntax deprecation (solved by pre-execution validation) - Ungraceful PostgreSQL error handling (solved by SessionStart hook) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
3.2 KiB
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 |
/schema |
Show database/DataFrame schema |
/explain |
Explain dbt model lineage |
/lineage |
Visualize data dependencies |
/run |
Execute dbt models |
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_ROWSenvironment variable - Use
chunk_sizeparameter for large files - Monitor with
list_datatool
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.