npcpy — MCP Server by NPC-Worldwide

by NPC-Worldwide · MCP Server · ★ 1.4k

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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. Build multi-agent teams and simplify context engineering through the NPC Context-Agent-Tool data layer which ensures compliance through software rather than prompts. Quick Examples Create and use personas My friend, you speak of the highlands where our liberty is carved in stone. If we must speak of the most critical territory to hold within these mountains, it is the Viceroyalty of Peru and the heart of the Republic of Gran Colombia united. To lose the passes of the Andes or the cities of Lima and Quito would be to hand the crown

agentsaillmmcpmcp-clientmcp-serverollamaperplexitypythonsql

Quick Facts

Stars1,400
Forks103
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score49.76/100
Open Issues12
Last Updated2026-06-20
Created2024-09-27
Platformscli, mcp, python
Est. Tokens~22k

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Frequently Asked Questions

What is npcpy?

npcpy is The python library for research and development in NLP, multimodal LLMs, Agents, ML, Knowledge Graphs, and more.. It is categorized as a MCP Server with 1.4k GitHub stars.

What programming language is npcpy written in?

npcpy is primarily written in Python. It covers topics such as agents, ai, llm.

How do I install or use npcpy?

You can find installation instructions and usage details in the npcpy GitHub repository at github.com/NPC-Worldwide/npcpy. The project has 1.4k stars and 103 forks, indicating an active community.

What license does npcpy use?

npcpy is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to npcpy?

The top alternatives to npcpy on Agent Skills Hub include sdk-python, klavis, dbhub. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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