npcpy: The python library for research and development in NLP, multimodal LLMs, Agents, ML, Knowledge Graphs

by NPC-Worldwide · MCP Server · ★ 1.5k

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

How to install npcpy

pip install npcpy

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

Security audit verdict: SAFE · quality 66/100

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.

agentsaillmmcpmcp-clientmcp-serverollamaperplexitypythonsql

Quick Facts

Stars1,523
Forks139
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score66/100
Open Issues7
Last Updated2026-11-02
Created2024-09-27
Platformscli, mcp, python
Est. Tokens~22k

About npcpy

npcpy is a library that provides key primitives for research and development with multimodal language models, agentic AI, and knowledge graphs. Its flexible framework makes it easy to engineer powerful AI applications with support for local (, , , ) and cloud providers.

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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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