by bonigarcia · MCP 服务器 · ★ 84
Context Engineering Context engineering can be defined as the practice of designing systems that provide a Large Language Model (LLM) and AI agents with all the necessary information to complete a task effectively. It goes beyond prompt engineering since it focuses on building a comprehensive and structured context from various sources like instructions, external knowledge, memory, tools, and state. The central idea is that the success of a complex LLM-based system depends more on the quality and completeness of the context provided than on the specific wording of the prompt itself.
| Stars | 84 |
| Forks | 15 |
| Language | Python |
| Category | MCP 服务器 |
| License | Apache-2.0 |
| Quality Score | 40.052/100 |
| Last Updated | 2026-06-17 |
| Created | 2025-10-16 |
| Platforms | mcp, python |
| Est. Tokens | ~17k |
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context-engineering is Context Engineering: Build Consistent, Accurate, Predictable AI Systems. It is categorized as a MCP 服务器 with 84 GitHub stars.
context-engineering is primarily written in Python. It covers topics such as agent-skills, agentic-ai, context-engineering.
You can find installation instructions and usage details in the context-engineering GitHub repository at github.com/bonigarcia/context-engineering. The project has 84 stars and 15 forks, indicating an active community.
context-engineering is released under the Apache-2.0 license, making it free to use and modify according to the license terms.