npcpy MCP Server

@cagostino

リポジトリ

基本情報

カテゴリ

その他

ライセンス

MIT

トランスポート

stdio

作者

cagostino

npcpy MCP Server について

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

#python #yaml #sql #ai #mcp #gemini #agents #perplexity #llm #anthropic #ollama #deepseek #mcp-server #mcp-client

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npcpy MCP Server のツール

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概要

What is npcpy?

npcpy is a Python library that provides key primitives for research and development with multimodal language models, agentic AI, and knowledge graphs. It supports both local providers (ollama, llama.cpp, onnx, LM Studio) and cloud providers, and enables building multi‑agent teams with a Context‑Agent‑Tool data layer that enforces compliance through software rather than prompts.

How to use npcpy?

Install with pip install npcpy. Then import the library to create NPC personas, run direct LLM calls, build agents with built‑in or custom tools, orchestrate multi‑agent debates via NPCArray, or manage knowledge graphs with sleep/dream lifecycle functions. Example code is provided for each major feature.

Key features of npcpy

Primitives for multimodal LLMs, agentic AI, and knowledge graphs
Support for local and cloud model providers
Multi‑agent debate and orchestration via NPCArray
Context‑Agent‑Tool data layer for safety compliance
Pre‑built agent tools: shell, Python, edit_file, web_search
CodingAgent for automated code execution

Use cases of npcpy

Build multi‑agent teams to debate and reach consensus on complex problems
Create persona‑based NPCs for interactive storytelling or simulations
Fine‑tune diffusion models with agent‑driven data collection and training
Simplify context engineering for large language model applications
Generate and execute code with the auto‑executing CodingAgent

よくある質問

What is the NPC Context-Agent-Tool data layer?

It is a framework within `npcpy` that structures interactions between personas (NPCs), agents, and tools to ensure compliance with directives through software rather than relying solely on prompts.

How do I install npcpy?

Run `pip install npcpy` in your environment.

What model providers does npcpy support?

`npcpy` supports local providers such as `ollama`, `llama.cpp`, `onnx`, and `LM Studio`, as well as cloud providers (e.g., `ollama`’s cloud models).

How do I run multi-agent debates with npcpy?

Use the `NPCArray` class to create a team of `NPC` objects, then call `team.infer()` with a prompt, optionally followed by `chain()` for iterative refinement. The README includes a full example with role‑based personas and debate rounds.

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