Claude MCP Data Engineer Server

A Model Context Protocol (MCP) server built for data engineers — gives Claude powerful tools to help with SQL, DBT, Snowflake, CSV analysis, pipeline validation, and ETL lineage.

Tools Available

Tool	Description
format_sql	Format & prettify SQL queries with proper indentation
json_to_ddl	Generate CREATE TABLE DDL from a JSON sample record
analyze_csv	Analyze CSV data — row count, column types, null counts
generate_dbt_model	Generate a dbt model SQL file with source + deduplication CTE
validate_pipeline_config	Validate a data pipeline JSON config for required fields
generate_snowflake_table	Generate a Snowflake CREATE TABLE with optional CLUSTER BY
summarize_etl_lineage	Summarize ETL lineage JSON into a human-readable pipeline flow

Setup

1. Install dependencies

pip install -r requirements.txt

2. Run the MCP server

python -m src.server

3. Connect to Claude Desktop

Add this to your claude_desktop_config.json (~/AppData/Roaming/Claude/ on Windows):

{
  "mcpServers": {
    "data-engineer": {
      "command": "python",
      "args": ["-m", "src.server"],
      "cwd": "C:/Users/Nikhil/claude-mcp-data-engineer"
    }
  }
}

Example Usage

Format SQL

Ask Claude:

"Format this SQL: select id,name from users where status='active' group by id"

Generate DDL from JSON

Ask Claude:

"Generate a CREATE TABLE DDL for this JSON: {"id": 1, "name": "Nikhil", "salary": 95000.0, "joined": "2024-01-15"}"

Analyze CSV

Ask Claude:

"Analyze this CSV data and tell me column types and null counts"

Generate DBT Model

Ask Claude:

"Generate a dbt model for source 'raw', table 'orders', columns: id, customer_id, amount, created_at"

Validate Pipeline Config

Ask Claude:

"Validate this pipeline config: {"source": {"type": "snowflake"}, "destination": {"type": "s3"}, "schedule": "0 2 * * *"}"

Tech Stack

• Python 3.10+
• MCP SDK (mcp[cli])
• FastMCP for server definition

Author

Nikhil E — Sr. Data Engineer | BI Architect GitHub: itsnikhile