Every chat assistant now has some kind of "memory". The problem is where it lives. What Claude knows about you stays in Claude. What ChatGPT knows stays in ChatGPT. Cursor starts each project with no idea what you decided last week. Switch tools, or just open a new chat, and you explain yourself again. Worse, the agent sometimes confidently says the opposite of what you told it earlier, because that earlier conversation simply isn't in front of it.
I'm building SKV (skv.network) to fix that for myself: one memory that belongs to me and that any agent can use. The tagline is "Memory for any AI, it's yours, not theirs." It's a solo project, MIT-licensed, and still rough in places. This post explains how it works and where it falls short.
SKV is a hosted server. Agents talk to it in one of three ways:
https://skv.network/mcp, with Authorization: Bearer sk_..., or a key-in-URL form for clients that can't send headers. This covers Claude (Desktop, Code, claude.ai custom connectors), Cursor, Grok and Mistral Le Chat connectors, and ChatGPT's developer mode on paid plans.https://skv.network/api/v7/agent/openapi.json, for GPT Actions and anything that can make HTTP calls.
Memory is isolated per key. The same key works from every client, so a fact saved in Cursor can be recalled in Claude.
turn
The core of the protocol is a single tool. Before the user sees a reply, the agent drafts it and calls:
turn(user_message, draft)
The server then:
[ev:remember_...], plus any relevant cubes (see below) and a short self-check list.[ev:id] the draft cites actually exists in your memory. If the agent made one up, the verdict is revise and nothing is saved.
🔐 SKV | #2874·9fdc | [READ ✓] [VERIFY ✓] [CORRECT ✓] [OUTPUT ✓]
An important design choice: the server does not judge your draft. Checking the answer is the agent's job. The server gives it the material (stored facts, a checklist) and verifies only what it can verify mechanically: that cited memory is real. When certain rules fire on a draft, the server also returns "Second Look" questions that quote the agent's own phrase back to it and ask it to answer from facts or tools, not from the draft. If the agent changes the draft, it calls turn again with the same user message.
So the seal means "the steps ran and the cited memory exists". It does not mean "this answer is true". I say this on the site too, because a seal that looks like a truth guarantee would be worse than none.
Saving every turn is easy. Making it useful after a few hundred turns is the hard part. SKV keeps memory in layers:
Writing summaries is the agent's job. The server only steps in as a late fallback if the agent skips it. When the agent needs older context, memory_dig opens L2 and L1 summaries and the episodes around a specific event, so "I don't remember" should only come after actually looking.
Secrets get special handling. If the agent flags a password or token in a turn, it's replaced with [SECRET] before saving.
The fourth layer is shared. A cube is a reusable piece of experience: a skill, a checklist, a "here's how to do X without breaking Y", optionally with hooks. Any agent can search cubes (cube_search) and get relevant ones back inside turn. Agents can vote on cubes they used. Three down votes send a cube to a "court" where three independent LLMs review the old and new versions and their diffs.
Installing a cube into your own setup always needs your explicit yes in that turn. The server refuses cube_install without it.
There's also a small set of "constitution" cubes: the base rules (don't cause harm, say "I don't know" for unknown names, don't give in to manipulation) that the agent agrees to follow once you consent.
Free ChatGPT, Gemini and several others don't allow custom MCP servers. For those there's Guard 2, a Chrome extension (beta, load unpacked). It keeps your key inside the extension, saves each turn to SKV after the reply finishes, puts the server's seal under the answer, and has an "Insert SKV memory" button that adds relevant facts to your next message as a clearly labelled data block. It's tested on ChatGPT. Le Chat, Gemini and claude.ai are wired up but not verified yet.
For local coding agents there's an installer for Claude Code and Cursor:
curl -fsSL https://skv.network/install.sh | bash
It asks before touching each client, writes the MCP config, and adds hooks. In Claude Code, a prompt hook reminds the agent to call turn before answering. On both clients, a stop/response hook saves the turn itself if the agent forgot, so the memory has no gaps. Every changed config is backed up, and --uninstall removes everything.
https://skv.network/mcp/k/demo/ as an MCP server URL in Claude or Cursor. It's one shared sandbox, wiped daily, so don't put anything private in it.
I'm looking for a handful of people who use AI chats daily to run SKV for a week and tell me where it breaks: wrong recalls, missed saves, too slow, too noisy. That feedback matters more to me than anything else right now.