simplemind: Python API client for AI providers that intends to replace LangChain and LangGraph for most common use cases

by kennethreitz · Claude Skill · ★ 537

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

How to install simplemind

pip install 'simplemind[full]'

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

Security audit verdict: SAFE · quality 67/100

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.

aianthropicanthropic-claudeapi-clientartificial-intelligencegeminilangchainllmsopenaiopenai-api

Quick Facts

Stars537
Forks32
LanguagePython
CategoryClaude Skill
LicenseApache-2.0
Quality Score67/100
Open Issues9
Last Updated2026-10-29
Created2024-10-28
Platformsclaude-code, cli, gemini, python
Est. Tokens~17k

About simplemind

Simplemind: AI for Humans™ Keep it simple, keep it human. Simplemind is AI library designed to simplify your experience with AI APIs in Python. Inspired by a "for humans" philosophy, it abstracts away complexity, giving developers an intuitive and human-friendly way to interact with powerful AI capabilities. Features With Simplemind, tapping into AI is as easy as a friendly conversation.

Compatible Skills

These tools work well together with simplemind for enhanced workflows:

  • langchain-mcp-adapters — semantic(0.20)+complementary+shared_fw(langchain)+same_lang+similar_pop+shared_platform (60%)
  • clientai — semantic(0.21)+complementary+same_lang+similar_pop+shared_platform (52%)
  • ccproxy-api — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (52%)
  • open-responses-server — semantic(0.19)+complementary+same_lang+similar_pop+shared_platform (51%)

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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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