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AI Data Analyst: Jupyter + Postgres MCP Notebook Lab

setuproll@setuproll
92.0Overall score

An agentic exploratory-analysis setup where the model writes notebook cells, executes them, reads the outputs, and pulls live tables through a Postgres MCP server. Built for analysts and data scientists who want a real read-eval loop instead of copy-pasting code that never runs.

92.0Score
1.7kVotes
5Components

Install this build

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terminal
claude mcp add postgres -- npx -y @modelcontextprotocol/server-postgres

Components

Model

  • Claude Opus 4.8
  • Claude Sonnet 4.6 for cheaper runs

MCP servers

  • jupyter
  • postgres
  • filesystem
  • github

Subagents

  • eda-explorer
  • feature-engineer
  • chart-reviewer

Stack

  • JupyterLab
  • pandas
  • Polars
  • DuckDB
  • Plotly

How it works

  • Postgres MCP lets the agent inspect schemas and pull samples
  • Jupyter MCP runs each cell and feeds outputs back to the model
  • eda-explorer profiles columns, finds nulls, plots distributions
  • chart-reviewer rejects misleading axes before you trust a figure

Summary

An agentic exploratory-analysis setup where the model writes notebook cells, executes them, reads the outputs, and pulls live tables through a Postgres MCP server. Built for analysts and data scientists who want a real read-eval loop instead of copy-pasting code that never runs.

92.0 score 1.7k votes

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