by brycewang-stanford · MCP Server · ★ 240
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
English | 中文 StatsPAI: Agent-Native Causal Inference & Econometrics Toolkit for Python [](https://doi
| Stars | 240 |
| Forks | 44 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 46.936/100 |
| Open Issues | 4 |
| Last Updated | 2026-06-21 |
| Created | 2025-07-26 |
| Platforms | mcp, python |
| Est. Tokens | ~25k |
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StatsPAI is 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 . It is categorized as a MCP Server with 240 GitHub stars.
StatsPAI is primarily written in Python. It covers topics such as agent-native, ai-agents, causal-discovery.
You can find installation instructions and usage details in the StatsPAI GitHub repository at github.com/brycewang-stanford/StatsPAI. The project has 240 stars and 44 forks, indicating an active community.
StatsPAI is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to StatsPAI on Agent Skills Hub include BambooAI, web-agent-protocol, Containarium. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.