Memdex — Shared Memory for All Your AI Tools

What

Memdex is a browser extension that creates a shared memory layer across multiple AI tools, including ChatGPT, Claude, Gemini, Perplexity, and Grok. It is built for people who work across several AI assistants and want to reuse past context, decisions, preferences, and project details without re-explaining them in every new chat.

The product’s core workflow is capture, process, retrieve, and inject. It automatically records supported AI conversations locally on the user’s device, extracts compact reusable memories from those chats, and suggests relevant context that can be inserted into later prompts across tools. Based on the page, Memdex appears positioned as a personal productivity and workflow utility for heavy AI users rather than a full standalone AI assistant.

Features

• Automatic conversation capture: Memdex can auto-record chats from supported AI platforms in the background, reducing manual saving and helping preserve working context.
• Memory extraction from chat logs: It turns raw conversations into reusable memories such as preferences, decisions, facts, and project details, making prior work easier to reuse.
• Semantic context retrieval: The system matches relevant memories to a new prompt so users can bring in useful background without searching through old chats.
• Cross-tool context injection: Users can add remembered context into major AI platforms with native buttons and use shortcuts for other text boxes, supporting continuity across tools.
• Local-first storage: The page states that memories are stored locally and encrypted on the device, which is valuable for users who want tighter control over sensitive working context.
• Saved chats and continuation workflow: Users can keep full conversations locally and continue previous discussions by selecting a saved chat title when they need the original thread, not just extracted memory.

Helpful Tips

• Assess fit based on AI workflow complexity: This type of product is most useful for teams or individuals who actively switch between several AI tools and repeatedly restate project context.
• Distinguish chat archive from reusable memory: Memdex separates full saved conversations from extracted memories, so buyers should confirm which mode best supports their working style and audit needs.
• Validate browser and platform coverage early: The page names Chromium-based browsers and several major AI platforms, so organizations using Safari, Firefox, or niche AI apps should plan around current support limits.
• Review privacy assumptions carefully: The site emphasizes local storage and no model training on user data, but buyers considering sync features should examine how optional cross-device behavior is implemented when available.
• Start with high-repeat workflows: Adoption is likely easier when first applied to recurring tasks such as campaign planning, candidate screening, research synthesis, or project handoffs where context reuse is measurable.

OpenClaw Skills

Within the OpenClaw ecosystem, Memdex could serve as a memory source for agents that need continuity across sessions and model endpoints. A likely use case would be an OpenClaw skill that pulls relevant Memdex memories before launching a research, writing, PM, recruiting, or customer-support workflow, so the agent starts with prior preferences, decisions, and project context rather than a blank slate. The source page does not describe a native OpenClaw integration, so this should be treated as an inferred workflow pattern rather than a confirmed connector.

This combination could be especially useful for knowledge workers who coordinate across many AI systems and long-running initiatives. For example, OpenClaw agents could likely use Memdex-derived context to draft campaign assets consistent with earlier brand direction, generate hiring interview prompts aligned with prior evaluation criteria, or continue product strategy work without losing prior reasoning. If implemented well, that kind of shared memory layer could shift AI usage from isolated prompt sessions toward more persistent, multi-agent operational workflows.