MemoryPlugin gives you one persistent memory across OpenClaw, ChatGPT, Claude, and Gemini. It connects a single Chrome extension to inject context, search past conversations, and sync Chrome and X/Twitter bookmarks.
The OpenClaw memory plugin, now called Maximem Vity for OpenClaw, is a persistent memory solution designed for developers and AI power users who rely on OpenClaw for coding and other tasks. It eliminates the frustration of starting from scratch in every new session by providing a unified memory vault that works across OpenClaw, ChatGPT, Claude, and Gemini. Its core value lies in making your AI agent remember your preferences, past decisions, and project context, so you never have to re-explain yourself. By connecting via a simple npm package and a free API key, the plugin transforms OpenClaw into an agent with long-term recall, dramatically improving efficiency and consistency across all your interactions.
OpenClaw, despite being a powerful coding agent, suffers from a fundamental flaw: it has no persistent memory. Every new session is a blank slate, discarding everything you taught it in previous conversations. The built-in memory uses flat markdown files stored locally that are not semantically searchable and cannot be queried by meaning. Additionally, long conversations trigger context compaction, silently discarding early instructions and critical architectural decisions. Memory is also device-locked, so switching from your desktop to your laptop forces the agent to forget everything. Worse, ChatGPT, Claude, and Gemini each maintain completely separate memory stores, meaning what you teach one AI is invisible to all others, including OpenClaw. This fragmentation wastes time and forces users to repeat themselves constantly.
The first major feature group consists of Auto-Recall and Auto-Capture. Auto-Recall proactively injects relevant memories into every OpenClaw response before it runs, ensuring the agent has the context it needs without you having to ask. Auto-Capture automatically saves important context after every exchange, building a continuously updated knowledge base. Together, these features make memory seamless and effortless, eliminating the need for manual note-taking or copy-pasting. This is particularly valuable during long coding sessions where decisions build on one another, as the agent never loses the thread of the conversation.
The second major feature group is the semantic graph and vector similarity search. Under the hood, Maximem builds a semantic graph of everything your OpenClaw sessions produce—code decisions, architectural choices, preferences, and project context. Before each response, the plugin queries this graph using vector similarity to find the most relevant past memories. This means that even if you mentioned a specific coding pattern three sessions ago, the agent can retrieve it accurately based on meaning, not just keyword matches. The precision of this retrieval is reflected in Maximem's top scores on the LongMemEval benchmark, demonstrating industry-leading recall accuracy.
Publisher
A
admin
Launch Date2026-02-03
Platformweb
Pricingfreemium
Domain Authority
Ahrefs DR18/100