mcp-server

StatsPAI: Causal Inference Made Easy

Name: StatsPAI: Causal Inference Made Easy
Author: brycewang-stanford

Get unified causal inference with StatsPAI, a Python library for data-driven founders, with 274 GitHub stars.

274 stars55 forksPythonQuality 8/10Updated 7/12/2026100% free · open source

About this skill

StatsPAI is the first Agent-native Python library for causal inference and applied econometrics — unified API, broad cross-method coverage, structured result objects, machine-readable schemas, Skills, an MCP server, and R/Stata parity validation.

Topics

agent-native

ai-agents

causal-discovery

causal-inference

data-science

difference-in-differences

double-machine-learning

econometrics

instrumental-variables

llm

mcp

panel-data

policy-evaluation

python

regression-discontinuity

rstats

stata

statistics

synthetic-control

treatment-effects

What's inside — free to inspect

No purchase needed

Read the entire source before you build — unlike paid marketplaces that hide it behind a buy button.

top-level files

folders

31.3M

repo size

MIT

license

Key files

.pre-commit-config.yaml

README_CN.md

README.md

File tree

.cov_decomp/

.coverage_campaign/

.examples_campaign/

.github/

.tier_eg_campaign/

.tierd_campaign/

benchmarks/

docs/

examples/

papers/

plans/

rust/

schemas/

scripts/

specs/

src/

StatsPAI_full_data_analysis_skill/

test-notebooks/

tests/

tools/

.codespellrc

.flake8

.gitignore

.pre-commit-config.yaml

Quick Actions

Details

Creator

brycewang-stanford

Language

Python

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