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Add RAG, vector memory, model routing, and agent identity to AI apps.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "NeuralBrain" MCP server from askskill: Run: claude mcp add --transport http 'io-github-alexcurpan-cloud-neuralbrain' 'https://neuralbrain.ai/mcp'
Explain how to use NeuralBrain to add vector memory and RAG to a customer support chat assistant, including knowledge ingestion, retrieval flow, context assembly, and basic sample code.
An integration plan describing data ingestion, retrieval-augmented flow, and sample code structure.
Design a NeuralBrain-based model routing strategy: send simple Q&A to a low-cost model and complex reasoning to a high-performance model, with example rules and call flow.
A clear set of model routing rules, decision logic, and request handling flow.
Show how to use NeuralBrain to configure agent identity and access control for a multi-agent system, and explain best practices for team collaboration scenarios.
Implementation guidance for agent identity, permission boundaries, and multi-agent collaboration setup.
Lets AI agents search markdown knowledge files and run protocol checks.
High-performance memory system for AI agents with layered memory, RAG, and versioning.
Give AI agents local-first structured memory with search and timeline tracking.
Give AI coding assistants local long-term memory with searchable lessons and patterns.
Connect AI agents to secure RAG workflows across multiple vector databases.
Give language models persistent memory for onboarding, rule recall, and consistent coding.