context-engineering

by bonigarcia · MCP Server · ★ 95

About context-engineering

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.

agent-skillsagentic-aicontext-engineeringgenerative-aillmmcpmcp-servermemory-managementmulti-agent-systemsprompting

Quick Facts

Stars95
Forks16
LanguagePython
CategoryMCP Server
LicenseApache-2.0
Quality Score56.8982089715141/100
Last Updated2026-07-08
Created2025-10-16
Platformsmcp, python
Est. Tokens~17k

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Frequently Asked Questions

What is context-engineering?

context-engineering is Context Engineering: Build Consistent, Accurate, Predictable AI Systems. It is categorized as a MCP Server with 95 GitHub stars.

What programming language is context-engineering written in?

context-engineering is primarily written in Python. It covers topics such as agent-skills, agentic-ai, context-engineering.

How do I install or use 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 95 stars and 16 forks, indicating an active community.

What license does context-engineering use?

context-engineering is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

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