# Auto Causal Inference

> Use this tool when you need to uncover causal relationships in data, particularly in banking and customer behavior analysis, as it automates the process of identifying confounders, mediators, and effect modifiers, and estimates Average Treatment Effects. It takes treatment and outcome variables as input and generates causal graphs and plain-language business summaries as output. This tool is ideal for business analysts seeking to explore causal relationships in customer data without requiring extensive statistical knowledge.

Canonical page: https://skillsregistry.net/skills/lethienhoavn-auto-causal-inference  
JSON: https://api.skillsregistry.net/v1/skills/lethienhoavn-auto-causal-inference

## Description

This MCP server provides automated causal inference capabilities by combining LLM-guided variable classification with DoWhy statistical analysis on SQLite banking data. Built with Python using FastMCP, LangGraph, and OpenAI's GPT-3.5-turbo, it features a single tool that takes treatment and outcome variables, uses AI to classify other variables as confounders, mediators, effect modifiers, colliders, or instruments, generates causal graphs in DOT format, and executes DoWhy code to estimate Average Treatment Effects using backdoor adjustment with linear regression. The implementation includes both standalone agent and MCP server versions, automatically generates plain-language business summaries of causal effects, and works with predefined banking variables like customer demographics, engagement metrics, and Internet Banking activation, making it valuable for business analysts exploring causal relationships in customer data without requiring deep statistical expertise.

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/lethienhoavn-auto-causal-inference)
- **Repository:** <https://github.com/lethienhoavn/auto-causal-inference>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "lethienhoavn-auto-causal-inference"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/lethienhoavn-auto-causal-inference` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/lethienhoavn-auto-causal-inference/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt