Context-Engineering-for-Multi-Agent-Systems

by Denis2054 · Jupyter Notebook · ★ 224

Save thousands of lines of code by building universal, domain-agnostic Multi-Agent Systems (MAS) through high-level semantic orchestration. This repository provides a production-ready blueprint for the Agentic Era, allowing you to replace rigid, hard-coded workflows with a dynamic transparent Context Engine that provides 100% transparency.

#agentic-ai#agentic-rag#context-engineering#deterministic-ai#gpt-5-api#mcp#model-context-protocol#multi-agent-systems#pinecone#rag#semantic-analysis#semantic-blueprints#universal-context-engine

Install

git clone https://github.com/Denis2054/Context-Engineering-for-Multi-Agent-Systems.git

Claude Desktop config

Add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "context-engineering-for-multi-agent-systems": {
      "command": "npx",
      "args": [
        "-y",
        "github:Denis2054/Context-Engineering-for-Multi-Agent-Systems"
      ]
    }
  }
}

From the README

[](https://opensource.org/licenses/MIT) Move beyond prompting to build a Context Engine in a transparent architecture of context and reasoning [**🎞️▶️**](https://denis2054.github.io/Context-Engineering-for-Multi-Agent-Systems/media/player.html) **In 21st‑century Agentic AI, Natural‑Language‑Programmed LLMs are the execution agents, and the domain‑agnostic dual‑RAG MAS is the environment they operate in.** This repository provides a production-ready blueprint for the Agentic Era, allowing you to replace rigid, hard-coded workflows with a dynamic, **transparent**, **observable**, and **sovere…

Read full README on GitHub →