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sql-database-pipeline

v0.1.1

Build SQL database pipelines with dlt: connect to any SQL source, load tables to a destination, tune performance with backends

Claude Code8 Skills1 MCP serverstdio

By ScaleVector GmbHLicense: https://github.com/dlt-hub/dlthub-ai-workbench/blob/master/LICENSE59 GitHub starsUpdated 5 days ago

Directory evidence

Runtimes
Claude Code
Parsed components
9 skill or MCP entries
Source updated
Sep 18, 2026
Manifest status
Canonical path parsed

The directory validates manifest shape and source location. It does not execute the plugin or provide a security endorsement. Review the indexing methodology →

Install sql-database-pipeline for Claude Code

Installs for the current user
claude plugin marketplace add IchenDEV/agent-plugin-mkt
claude plugin marketplace update agent-plugin-marketplace
claude plugin install sql-database-pipeline@agent-plugin-marketplace

Paste and run these commands in a terminal with Claude Code. They add and refresh the PluginsMP catalog, then install this plugin.

The installer fetches third-party code from the source repository shown on this page. This directory validates manifest structure and source location, but does not perform a security audit; review the manifest, components, and source before installing.

Get the source manually
git clone https://github.com/dlt-hub/dlthub-ai-harness

Clone the source repository, then follow its setup instructions to add the plugin to a compatible client. The plugin root is workbench/sql-database-pipeline/.

Plugin files

workbench/sql-database-pipeline/
├── .claude-plugin/plugin.json
├── skills/add-table/SKILL.md
├── skills/adjust-table/SKILL.md
├── skills/create-sql-database-pipeline/SKILL.md
├── skills/debug-pipeline/SKILL.md
├── skills/find-source/SKILL.md
├── skills/optimize-sql-performance/SKILL.md
├── skills/validate-data/SKILL.md
├── skills/view-data/SKILL.md
└── .mcp.json

Included Skills8

add-tableskills/add-table/SKILL.md

Add a new table or view to an existing dlt SQL database pipeline. Use when the user wants to load additional tables from the same database that already has a working pipeline.

adjust-tableskills/adjust-table/SKILL.md

Adjust a working dlt SQL database pipeline for production — remove dev limits, add incremental loading, configure merge keys. Use when the user wants to remove .add_limit(), load the full table, or set up incremental loading on a cursor column. For speed/memory tuning (backend, chunk size, parallelism) use optimize-sql-performance instead. For inspecting loaded data or fixing column types/schema after a load, use validate-data instead.

create-sql-database-pipelineskills/create-sql-database-pipeline/SKILL.md

Create a dlt pipeline from a SQL database source (postgres, mysql, mssql, oracle, sqlite, or any SQLAlchemy-supported database). Use when the user wants to load tables from a relational database to a destination like DuckDB, BigQuery, or Snowflake. Not for REST APIs or file sources.

debug-pipelineskills/debug-pipeline/SKILL.md

Debug and inspect a dlt SQL database pipeline after running it. Use after a pipeline run (success or failure) to inspect traces, load packages, schema, and diagnose errors like connection failures, missing credentials, driver issues, or failed jobs.

find-sourceskills/find-source/SKILL.md

Find and explore a SQL database source for a dlt pipeline. Use when the user wants to load data from a relational database (postgres, mysql, mssql, oracle, sqlite, or any SQLAlchemy-supported database), mentions a database connection, wants to discover available tables, or asks to build a pipeline from a SQL source.

optimize-sql-performanceskills/optimize-sql-performance/SKILL.md

Speed up a dlt SQL database pipeline. Use when extraction from a relational database (postgres, mysql, mssql, oracle, snowflake, etc.) is slow or memory-heavy and the user wants to optimize it — pick a faster backend, tune chunk size, parallelize tables, or reduce reflection overhead. For first-time incremental/merge setup or removing .add_limit() use adjust-table instead.

validate-dataskills/validate-data/SKILL.md

Validate schema and data after a successful dlt SQL database pipeline load. Use when the user wants to check if loaded data looks correct, inspect table schemas, fix data types, or verify column mappings from the source database.

view-dataskills/view-data/SKILL.md

Query, explore, or view data loaded by a dlt SQL database pipeline. Use when the user asks to query data, explore loaded tables, check row counts, write Python that reads pipeline data, or asks questions like "show me the data", "what users are there", "how much did we spend". Covers dlt dataset API, ibis expressions, and ReadableRelation. NOT for querying the source database — use the pipeline's destination.

MCP servers1

dlt-workspace-mcpstdio
command
uv
args
run dlthub ai mcp --stdio

Plugin manifests1

workbench/sql-database-pipeline/.claude-plugin/plugin.json
{
  "name": "sql-database-pipeline",
  "description": "Build SQL database pipelines with dlt: connect to any SQL source, load tables to a destination, tune performance with backends",
  "version": "0.1.1",
  "author": {
    "name": "ScaleVector GmbH"
  },
  "homepage": "https://dlthub.com/docs",
  "repository": "https://github.com/dlt-hub/dlthub-ai-workbench",
  "license": "https://github.com/dlt-hub/dlthub-ai-workbench/blob/master/LICENSE",
  "keywords": [
    "dlthub",
    "etl",
    "data-pipeline",
    "python",
    "sql",
    "database"
  ],
  "mcpServers": {
    "dlt-workspace-mcp": {
      "command": "uv",
      "args": [
        "run",
        "dlthub",
        "ai",
        "mcp",
        "--stdio"
      ]
    }
  }
}

For maintainers

If you maintain this plugin, link to this source-backed listing from your README so users can review its manifest and indexed components.

[sql-database-pipeline on Agent Plugins Marketplace](https://pluginsmp.com/plugins/sql-database-pipeline)