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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.
Give LLM agents persistent memory, personality, and context management.
Give AI coding assistants local long-term memory with searchable lessons and patterns.
Provide persistent memory, semantic search, and unified LLM routing for AI agents.
Connect AI agents to secure RAG workflows across multiple vector databases.
Run a self-hosted, traceable memory layer and MCP server for AI agents.
Give language models persistent memory for onboarding, rule recall, and consistent coding.