StatsPAI

brycewang-stanford/StatsPAI

★ 226 stars Python AI/LLM Updated 3d ago

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, an MCP server, and R/Stata parity validation.

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Quick Install

Copy the config for your editor. Some servers may need additional setup — check the README.

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "statspai": {
      "command": "uvx",
      "args": [
        "statspai"
      ]
    }
  }
}

Or install with pip: pip install statspai

README Excerpt

<p align="center"> <img src="https://raw.githubusercontent.com/brycewang-stanford/StatsPAI/main/docs/logo/readme-1.png" alt="StatsPAI - validation-tiered causal inference for Python" width="780"> </p> StatsPAI is a **validation-tiered** Python library for causal inference and applied econometrics. One `import`, **1,000+ registered functions** across **80+ submodules** (live count: `python scripts/registry_stats.py`), spanning classical econometrics, ML/AI causal methods, and reporting utilities

Tools (20)

aggtebartik_weightbayesian_synthbiprobitblock_weightsclogitcluster_synthdescribeebalanceesttabetregressfdidfracregfrontierglmgmmheckmankdensitylisa_cluster_maplpoly

Topics

agent-nativeai-agentscausal-discoverycausal-inferencedata-sciencedifference-in-differencesdouble-machine-learningeconometricsinstrumental-variablesllmmcppanel-datapolicy-evaluationpythonregression-discontinuity

StatsPAI

Quick Install

README Excerpt

Tools (20)

Topics

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