The Context-First AGI Cognitive Context Engine (CCE) Prototype provides a robust toolkit for developers to implement context-aware AI agents. It leverages vector embeddings to store historical user interactions, enabling efficient retrieval of relevant context snippets. The engine automatically summarizes lengthy conversations to fit within LLM token limits, ensuring continuity and coherence in multi-turn dialogues. Developers can configure context prioritization strategies, manage memory lifecycles, and integrate custom retrieval pipelines. CCE supports modular plugin architectures for embedding providers and storage backends, offering flexibility for scaling across projects. With built-in APIs for storing, querying, and summarizing context, CCE streamlines the creation of personalized conversational applications, virtual assistants, and cognitive agents that require long-term memory retention.

Nagato AI is an extensible AI agent framework that orchestrates autonomous workflows by combining task planning, memory management, and tool integrations. Users can define custom tools and APIs, allowing the agent to retrieve information, perform actions, and maintain conversational context over long sessions. With its plugin architecture and conversational UI, Nagato AI adapts to diverse scenarios—from research assistance and data analysis to personal productivity and automated customer interactions—while remaining fully open-source and developer-friendly.

MemoryPlugin adds long-term memory to your AI chats, letting tools like ChatGPT, Claude, Gemini, and others remember important details across conversations. This reduces the need to repeat information and enhances the personalization and efficiency of your interactions with AI. By using the Chrome extension and connecting through memoryplugin.com, you can manage what the AI remembers and ensure that your chats are always built on a consistent knowledge base, leading to better and faster assistance.

Agent Starter Pack is a developer toolkit that scaffolds intelligent, interactive agents on Google Cloud. It offers templates in Node.js and Python to manage conversation flows, maintain long-term memory, and perform tool and API invocations. Built on Vertex AI and Cloud Functions or Cloud Run, it supports multi-step planning, dynamic routing, observability, and logging. Developers can extend connectors to custom services, build domain-specific assistants, and deploy scalable agents in minutes.