by Denis2054 · MCP Server · ★ 231
Context Engineering for Multi-Agent Systems Move beyond prompting to build a Context Engine in a transparent architecture of context and reasoning 🎞️▶️ 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 sovereign Context Engine.
| Stars | 231 |
| Forks | 79 |
| Language | Jupyter Notebook |
| Category | MCP Server |
| License | MIT |
| Quality Score | 39.716/100 |
| Open Issues | 1 |
| Last Updated | 2026-05-11 |
| Created | 2025-09-01 |
| Platforms | mcp |
| Est. Tokens | ~616k |
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Context-Engineering-for-Multi-Agent-Systems is 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 th. It is categorized as a MCP Server with 231 GitHub stars.
Context-Engineering-for-Multi-Agent-Systems is primarily written in Jupyter Notebook. It covers topics such as agentic-ai, agentic-rag, context-engineering.
You can find installation instructions and usage details in the Context-Engineering-for-Multi-Agent-Systems GitHub repository at github.com/Denis2054/Context-Engineering-for-Multi-Agent-Systems. The project has 231 stars and 79 forks, indicating an active community.
Context-Engineering-for-Multi-Agent-Systems is released under the MIT license, making it free to use and modify according to the license terms.