It took my AI months to learn how I think, code, and ship. When a teammate joined the project, their AI started from zero β same codebase, same conventions, none of the context.
So I built memshare: peer-to-peer AI memory sharing, with consent on both sides.
Every AI tool today treats memory as a product feature locked inside one account. Claude remembers things for you. ChatGPT remembers things for you. Nobody else can get at it β not your teammate, not your other tools, not even you in a greppable format.
That means:
memshare treats AI memory as a data type β plain JSON files you own β not a feature of someone else's chat product.
npm install -g memshare-mcp
memshare init
Connect it to your AI tool once, and capture happens in conversation:
"we went with Postgres β the JSONB support decided it"
β the AI calls memory_set, saved as private
"what do you know about this project?"
β the AI calls memory_get
No commands to run. No copy-pasting. Your AI saves what it learns as you work.
When you want to share context with a teammate:
memshare export --tags "project-x,architecture" --for alice --preview
memshare export --tags "project-x,architecture" --for alice --expires 30d
Send that file however you want β Slack, email, AirDrop. On Alice's machine:
memshare preview bundle-a3f8c2d1.memshare.json # look, import nothing
memshare import bundle-a3f8c2d1.memshare.json # choose item by item
Alice picks each item individually. Everything lands private β receiving context is not consent to pass it on.
This is the part I care most about. Sharing someone's AI context without their control is a terrible idea. memshare has four gates:
private or shareable. Private items never leave, even if their tags match an export.--preview runs the same code path as the real export β there's no separate preview implementation that can drift.
memshare uses MCP (Model Context Protocol), which means it works with any MCP client:
// Cursor / Windsurf / GitHub Copilot β add to your MCP config
{
"mcpServers": {
"memshare": {
"command": "npx",
"args": ["-y", "memshare-mcp", "serve"]
}
}
}
claude mcp add memshare --scope user -- npx -y memshare-mcp serve
A designer in Cursor can hand component conventions to backend devs in Claude Code, and get the API contract back. Different people, different tools, same bundle format.
~/.memshare/memories/*.json
the actual product β plain JSON files
β² β² β²
β β β
MCP server CLI (future adapters)
β
Claude Β· Cursor Β· VS Code Β· Windsurf Β· any MCP client
The memory store is the product. The MCP server is one adapter over it, the CLI is another. If MCP disappears tomorrow, your data is still sitting in a folder β human-readable, diffable, git-friendly.
~/.memshare/
βββ config.json
βββ memories/
β βββ mem_<uuid>.json # one file per memory
βββ bundles/
βββ bundle_<id>.memshare.json
No database. No server. grep works. diff works. git works.
The honest risk: nothing in MCP can force a model to call a tool, so capture can quietly fail. memshare makes that visible:
memshare stats
12 memories, 5 in the last 14 days
βββββ ββ 14d ago β today
- 9 captured by an assistant, 3 added by hand
- 5 shareable, 7 private
A flat line means capture isn't firing, and you know within days.
import { MemoryStore, selectForExport, planImport } from "memshare-mcp";
const store = new MemoryStore();
await store.add({
content: "Team chose Postgres over MySQL",
tags: ["db"]
});
const { included, blocked } = await selectForExport(store, {
tags: ["db"]
});
Preview and the real action share one code path. selectForExport and planImport compute what would happen; the CLI renders that and then acts on it. No parallel implementation for a preview β consent based on a stale preview is not consent.
git clone https://github.com/kampana/memshare.git
cd memshare && npm install && npm run build
bash examples/try-it.sh
The script builds two fake stores in a temp directory and runs the full flow β capture, PII blocking, export, per-item import β then cleans up. Nothing touches your real config.
Or just install it:
npm install -g memshare-mcp
memshare init
Open source, MIT licensed, no server, no signup.
I'd love feedback β especially on the consent model and whether the sharing flow feels right. Issues and PRs welcome.