Memory for AI Agents in 6 lines of code
Agentic AI Framework for Java Developers
📑 PageIndex: Document Index for Reasoning-based RAG
MineContext is your proactive context-aware AI partner（Context-Engineering+ChatGPT Pulse）
Data transformation framework for AI. Ultra performant, with incremental processing. 🌟 Star if you like it!
🔥 Comprehensive survey on Context Engineering: from prompt engineering to production-grade AI systems. hundreds of papers, frameworks, and implementation guides for LLMs and AI agents.
Auto-Manage Your Personal Task Context with AI.
🧠 Make your agents learn from experience. Based on the Agentic Context Engineering (ACE) framework.
ApeRAG: Production-ready GraphRAG with multi-modal indexing, AI agents, MCP support, and scalable K8s deployment
Ultimate Context Engineering Infrastructure, starting from MCPs and Integrations
One Place for Agents to Store, Observe, and Learn. Context Data Platform for Self-learning Agents, designed to simplify context engineering and improve agent reliability and task success rates.
🧠 Context Engineering Research - Not just another agent collection, but using research and context engineering to function as a collective. Hub-and-spoke coordination through Claude Code.
🧠🔗 From idea to production in just few lines: Graph-Based Programmable Neuro-Symbolic LM Framework - a production-first LM framework built with decade old Deep Learning best practices
CTX: a tool that solves the context management gap when working with LLMs like ChatGPT or Claude. It helps developers organize and automatically collect information from their codebase into structured documents that can be easily shared with AI assistants.
Asking yours data in a natural language way through pre-modeling (data models and semantic models).
AI Agent that researches the lives of historical figures and extracts events into structured JSON timelines using LangGraph multi-agent orchestration.
PowerMem: Your AI-Powered Long-Term Memory — Accurate, Agile, Affordable.
An agentic workflow tool that provides context engineering support for opencode
A minimalist MVP demonstrating a simple yet profound insight: aligning AI memory with human episodic memory granularity. Shows how this single principle enables simple methods to rival complex memory frameworks for conversational tasks.
Packmind seamlessly captures your engineering playbook and turns it into AI context, guardrails, and governance.
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