stata-code: Agent-native Stata bridge for empirical research — run DiD/IV/RDD and publication-ready tables from Claude

by brycewang-stanford · MCP Server · ★ 52

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install stata-code

claude mcp add stata-code --scope user -- uvx --from "stata-code[mcp]" stata-code-mcp
pip install stata-code

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 59/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

ai-agentsanthropicclaudedata-analysisdata-scienceeconometricsjupyterllmmcpmcp-server

Quick Facts

Stars52
Forks6
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score59/100
Last Updated2026-10-23
Created2026-04-29
Platformsclaude-code, mcp, python, vscode
Est. Tokens~21k

About stata-code

English | 中文 stata-code [](https://marketplace.visualstudio.com/items?itemName=brycewang-stanford.stata-code-v

Compatible Skills

These tools work well together with stata-code for enhanced workflows:

  • empiricalwiki — semantic(0.28)+complementary+rare_topics+same_lang+similar_pop+shared_platform (64%)
  • data-agent-skill — semantic(0.24)+complementary+rare_topics+same_lang+similar_pop+shared_platform (62%)
  • data2story-skill — semantic(0.17)+complementary+rare_topics+same_lang+similar_pop+shared_platform (61%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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