Engram gives AI agents persistent memory that actually works. Instead of dumping entire conversation histories into context (expensive) or maintaining files by hand (tedious), Engram automatically extracts, connects, and surfaces the right memories at recall time. Scores 79.6% on LOCOMO vs Mem0's 66.9%. Uses 30x fewer tokens than full context. Two commands to set up. Works with Claude Code, Cursor, and any MCP client. Open source, TypeScript, zero dependencies.see more
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Imagine your AI agent finally having a true, reliable memory—not just a short-term buffer, but a deep, accessible knowledge base that evolves with every interaction. That is precisely what Engram delivers. For too long, building truly intelligent agents has been hampered by the limitations of context windows. You either overload the system with massive, expensive conversation histories, burning through tokens unnecessarily, or you resort to tedious manual file management, trying to keep track of what matters. Engram completely bypasses this bottleneck by acting as the essential memory layer your AI has been missing. It intelligently observes interactions, automatically extracting the most critical pieces of information, connecting related concepts, and ensuring that when your agent needs to recall something specific, the *right* memory surfaces instantly. This isn't just about storage; it's about intelligent retrieval that drastically cuts down on operational costs while boosting accuracy. In real-world testing, Engram demonstrates superior performance, scoring significantly higher than comparable memory solutions, proving its efficacy in creating smarter, more context-aware agents without the usual overhead.
This power comes without the typical developer headache. Setting up persistent, functional memory for your AI agent is astonishingly simple, requiring just two straightforward commands to integrate into your workflow. Engram is built for the modern developer ecosystem, offering seamless compatibility whether you are using cutting-edge tools like Claude Code, the Cursor IDE, or any standard MCP client. Built entirely in TypeScript and boasting zero external dependencies, this solution champions efficiency and transparency. Furthermore, because it intelligently prioritizes and compresses information, Engram uses up to thirty times fewer tokens than simply dumping the entire conversation history into the context, leading to substantial cost savings and faster response times. By moving beyond simple chat logs to a structured, interconnected memory graph, Engram empowers you to build sophisticated, stateful AI applications that remember, learn, and adapt far more effectively than ever before, truly unlocking the next level of agent capability.