akshare: Elegant and simple financial data interface library for Python, built for human beings! 开源财经数据接口库

by akfamily · MCP Server · ★ 23.2k

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

How to install akshare

uv pip install akshare --upgrade
pip install akshare --upgrade

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 70/100

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. Full audit →

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.

academicakshareasset-pricingbondcurrencydatadata-analysisdata-sciencedatasetseconomic-data

Quick Facts

Stars23,234
Forks3,564
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score70/100
Last Updated2026-11-06
Created2019-10-01
Platformsmcp, python
Est. Tokens~16k

About akshare

资源分享:对于想了解更多财经数据与量化投研的小伙伴,推荐一个专注于财经数据和量化研究的知识社区。 该社区提供相关文档和视频学习资源,汇集了各类财经数据源和量化投研工具的使用经验。 有兴趣深入学习的朋友可点此了解更多,也推荐大家关注微信公众号【数据科学实战】。 重磅推荐:AKQuant 是一款专为 量化投研 (Quantitative Research) 打造的高性能量化回测框架。它以 Rust 铸造极速撮合内核, 以 Python 链接数据与 AI 生态,旨在为量化投资者提供可靠高效的量化投研解决方案。参见AKQuant 工具推荐:期魔方是一款本地化期货量化分析工具,适合数据分析爱好者使用。无需复杂部署,支持数据分析和机器学习功能,研究功能免费开放。 如需了解更多信息可访问期魔方。...

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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:

View on GitHub → Browse MCP Server tools