Denis2054/Context-Engineering-for-Multi-Agent-Systems

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.

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Established

This project provides a robust framework to build AI systems that manage multiple AI agents for complex tasks. It takes high-level goals and automatically orchestrates various AI agents to deliver structured outputs, detailed reasoning, and cost analysis. This is designed for AI architects, data scientists, and engineers who build and deploy AI solutions and need transparency and control over multi-agent workflows.

188 stars.

Use this if you need to build flexible, observable, and adaptable AI systems that can handle diverse tasks without constant code changes.

Not ideal if you are looking for a simple, single-agent prompting tool for basic text generation.

AI-architecture workflow-automation AI-governance LLM-operations system-design
No Package No Dependents
Maintenance 10 / 25
Adoption 10 / 25
Maturity 15 / 25
Community 22 / 25

How are scores calculated?

Stars

188

Forks

59

Language

Jupyter Notebook

License

MIT

Last pushed

Feb 13, 2026

Commits (30d)

0

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