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·8 min read

Looking for a mem0 alternative? Here's how dropdat compares

mem0 stores facts for a single agent. dropdat captures whole AI conversations as portable capsules you can drop into ChatGPT, Claude, Cursor, Claude Code — and recall via MCP. Side-by-side comparison.

If you searched for a mem0 alternative, you probably ran into the same wall most people hit: mem0 stores extracted facts for a single agent runtime. The moment you switch from Cursor to Claude Code, from ChatGPT to Claude, from one project to another, the memory doesn't follow.

dropdat solves a different shape of the problem. Instead of extracting facts and replaying them inside one agent, it captures whole conversations as portable capsules and exposes them to every AI you use — through a browser extension on the web side and an MCP server on the coding-agent side.

What dropdat does that mem0 doesn't

When mem0 is the right fit

If you're building a single LLM application and want a memory layer that extracts facts, embeds them, and replays them at inference time, mem0 is purpose-built for that. It's a library you embed in your own app.

When dropdat is the right fit

If you, the human, work across multiple AI products every day and you keep losing context when you switch — dropdat is built for that. It's a product, not a library. You install the Chrome extension, capture chats with one click, and they're available everywhere.

A concrete example

You debug an issue with Claude. You open Cursor an hour later to fix it. Without dropdat, you re-paste the context. With dropdat, Cursor's MCP-backed agent can recall the Claude conversation directly: `Use dropdat_recall to find the discussion about the migration error from earlier today.`

Side-by-side

Try it

The fastest way to evaluate: install the extension, capture two or three chats from ChatGPT and Claude, then point Claude Code or Cursor at the dropdat MCP server. You'll feel the difference in 10 minutes.

Try dropdat free