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This way, an llm prompt includes not just the user’s latest query but also retrieved memory, preferences, history or task state Working of mcp at backend (server side) At its core, mcp is an open standard that defines the communication rules between ai models (clients) and external capabilities (servers) It creates a structured way for ai systems to discover, access, and interact with data and functionality provided by external sources. Whether you're switching between development, planning, or debugging environments, your ai assistants can access relevant memory without needing repeated instructions The openmemory mcp server ensures all memory stays local, structured, and under your control with no cloud sync or external storage. Part 1 of armo’s mcp server security series. Ai & memory mcp servers provide intelligent memory management and context retention capabilities for large language models These servers enable ai systems to store, retrieve, and utilize information across conversations and sessions. Instead of treating models as isolated entities, mcp enables a unified interface through which models can exchange data, context, and state information. To make that possible, companies are now turning to mcp servers as a key solution. It’s a new protocol from anthropic (released in late 2024) that gives llms structured access to your tools so they can reason, act, and stop hallucinating A shared language and structure that lets clients (like an llm agent) talk to servers (your tools, apis, and data sources) in a predictable way.