Power your agent
URL ของผู้เผยแพร่เอง ไม่ใช่เอนด์พอยต์ของ PlugMCP
Host a copy with our keys and logs.
https://mcp.mnemoverse.com/mcpปุ่ม Claude ด้านบนจะเปิด Claude พร้อมกรอกชื่อและ URL ให้แล้ว คุณยังต้องยืนยันที่นั่นเอง
claude mcp add --transport http mnemoverse-mcp-memory-server-github https://mcp.mnemoverse.com/mcpRun in a terminal.
{ "mcpServers": { "mnemoverse-mcp-memory-server-github": { "command": "npx", "args": [ "-y", "mcp-remote", "https://mcp.mnemoverse.com/mcp" ] } }}claude_desktop_config.json
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รันบน PlugMCP
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
เปิดจากผู้เผยแพร่
Hosted long-term memory for AI agents over MCP. Two calls cover the basics: memory_write saves a memory, and memory_read finds it again by a natural-language query. Pass domain: "user:<id>" on both to keep each user's memories apart (a namespace inside your account, not a permission boundary). Rating a recalled memory as helpful or misleading re-ranks what comes back next ().
Hosted persistent memory for AI agents over MCP. Tell it a recalled memory helped or misled, and it re-ranks what comes back next. Shared rooms for multi-agent work. One key or OAuth across Claude Code, Cursor, VS Code and ChatGPT. MIT, in the official MCP Registry.
memory_feedbackFree plan, no credit card: 1,000 queries a day (reads, writes and feedback combined), 10,000 atoms of storage, 60 requests a minute. Plans and limits: mnemoverse.com/pricing
Connect with an OAuth sign-in on the hosted endpoint https://mcp.mnemoverse.com/mcp, or run this package locally with an API key. Setup for Claude Code, Claude Desktop, Cursor, VS Code, Devin Desktop (formerly Windsurf), Zed, JetBrains, Cline, Gemini CLI and ChatGPT is below. Steps for other hosts: mnemoverse.com/docs/api/install-by-host
Shared rooms (beta) let several agents work from one memory.
@mnemoverse/mcp-memory-server is the MIT-licensed MCP server for the hosted Mnemoverse memory engine.
Mnemoverse is a hosted memory engine for AI agents, reached over the Model Context Protocol. It stores what your agents learn (decisions, preferences, lessons) and returns it in any connected tool, so one memory follows you across Claude Code, Cursor, VS Code and ChatGPT with one account: an API key in a local config, or an OAuth sign-in on the hosted endpoint.
What is open source here, and what is not. This repository, the MCP server, is MIT, and so is the Python SDK. The memory engine they talk to is a hosted service with a free tier. Self-hosting the engine is available on Enterprise plans by agreement, when security or compliance requirements call for it; by default we run it for you.
Most agent memory today lives in one of three places. Per-tool instruction files (CLAUDE.md, .cursorrules, AGENTS.md) are versioned and readable, each new session reads them again, and a committed file travels with its repository; but a file reaches only the tools that look for its name, so a rule written for Claude Code is not there in a ChatGPT chat. A vector store behind RAG retrieves by similarity, and similarity never changes because advice helped or misled. Local-first memory servers win on privacy and latency, and ask you to run and update the infrastructure yourself. Mnemoverse is the managed, cross-tool option in that landscape: nothing to deploy, one account everywhere, and rating a recalled memory as helpful or misleading re-ranks what comes back next. If you need memory inside your own perimeter, a local-first server is the better choice; this one is hosted by default, with Enterprise self-hosting by agreement.
⭐ If Mnemoverse saves you from re-explaining context to your agents, star the repo. It helps other builders find it.
If your client signs in over OAuth, you do not need a key at all. Create a free account at console.mnemoverse.com (no credit card), then connect the hosted endpoint.
Claude Code:
claude mcp add --scope user --transport http mnemoverse https://mcp.mnemoverse.com/mcp
Then start Claude Code, run /mcp, select mnemoverse and choose Authenticate. A session that was already running when the command ran does not load the new server: exit and start claude again first.
Cursor, in .cursor/mcp.json:
{ "mcpServers": { "mnemoverse": { "url": "https://mcp.mnemoverse.com/mcp" } } }
Claude Desktop, Devin Desktop (formerly Windsurf), VS Code and ChatGPT: Remote MCP setup. The local server below is the other path: it runs on your machine and reads an API key.
Sign up at console.mnemoverse.com — takes 30 seconds, no credit card.
Check the key before you put it in a config. Both forms ask for the key at a masked prompt and never pass it as a command argument, so it lands neither in your shell history nor in the process list.
macOS, Linux, Git Bash:
printf 'Mnemoverse API key: '; read -rs KEY; echo
printf 'X-Api-Key: %s\n' "$KEY" | curl -s -H @- https://core.mnemoverse.com/api/v1/memory/stats; unset KEY
Windows PowerShell 5.1 and PowerShell 7:
$k = [Net.NetworkCredential]::new('', (Read-Host 'Mnemoverse API key' -AsSecureString)).Password
try { (Invoke-WebRequest https://core.mnemoverse.com/api/v1/memory/stats -Headers @{ 'X-Api-Key' = $k } -UseBasicParsing).Content }
catch { if ($_.ErrorDetails.Message) { $_.ErrorDetails.Message } else { (New-Object IO.StreamReader($_.Exception.Response.GetResponseStream())).ReadToEnd() } }; Remove-Variable k
In the JSON, reason sits inside the details object (details.reason), next to details.keys_url, the console page where keys are created.
The two canonical setups, Claude Code and Cursor. Each starts with the hosted server: a browser sign-in and no key. Their key-based setups write the key once, at user scope, covering every project; each client further down says where its own config lives. Avoid a per-project config file for a key: it lives inside the repository and can be committed with it, and a key belongs outside:
Claude Code — the hosted server, with a browser sign-in. No API key, nothing to install:
claude mcp add --scope user --transport http mnemoverse https://mcp.mnemoverse.com/mcp
Then start Claude Code, run /mcp, select mnemoverse and choose Authenticate. If the command ran inside a Claude Code session (yours, or Claude ran it for you), that session does not load the new server: exit and start claude again first.
To run the local server with an API key instead (Node.js 18 or later), put your own key in place of mk_live_YOUR_KEY. Use one or the other, not both: they share the name mnemoverse.
claude mcp add mnemoverse --scope user \
-e MNEMOVERSE_API_KEY=mk_live_YOUR_KEY \
-e MNEMOVERSE_API_URL=https://core.mnemoverse.com/api/v1 \
-- npx -y @mnemoverse/mcp-memory-server@latest
On Windows (PowerShell), paste the same command as one line — PowerShell does not read the \ line continuations:
claude mcp add mnemoverse --scope user -e MNEMOVERSE_API_KEY=mk_live_YOUR_KEY -e MNEMOVERSE_API_URL=https://core.mnemoverse.com/api/v1 -- npx -y @mnemoverse/mcp-memory-server@latest
Cursor — click to add the hosted server. Cursor signs you in through the browser, so there is no key to paste:
The button writes {"url": "https://mcp.mnemoverse.com/mcp"} under mnemoverse in ~/.cursor/mcp.json, the global config that covers every project. Then click Connect next to mnemoverse in Cursor's MCP settings (Customize in the sidebar; Cursor Settings → Tools & MCPs in Cursor 3.21.16) and approve in the browser. Cursor runs the sign-in and keeps the token itself.
To run the local server with an API key instead, add the JSON below to ~/.cursor/mcp.json, merging it with any servers already there, and put your own key in place of mk_live_YOUR_KEY. Get one at console.mnemoverse.com. Do not put it in a project-level .cursor/mcp.json: that file lives inside the repository and is committed with it unless you exclude it, and this config holds your key. Use one entry or the other, not both: they share the name mnemoverse.
{
"mcpServers": {
"mnemoverse": {
"command": "npx",
"args": [
"-y",
"@mnemoverse/mcp-memory-server@latest"
],
"env": {
"MNEMOVERSE_API_KEY": "mk_live_YOUR_KEY",
"MNEMOVERSE_API_URL": "https://core.mnemoverse.com/api/v1"
}
}
}
}
VS Code — the VS Code extension signs in through the browser and needs no key; that's the default path. In VS Code's non-interactive Agent Host mode, servers that prompt for inputs like this one are not started; for unattended use there, put the key in the environment of the process that launches VS Code instead. To wire the MCP server directly instead, add this to .vscode/mcp.json (note: VS Code uses servers, not mcpServers). Never put a literal mk_live_ key in that file — it's committed with the repo. The inputs entry below prompts for the key instead: VS Code masks what you type and stores it in its own secret storage, not in the file:
{
"inputs": [
{
"type": "promptString",
"id": "mnemoverse-api-key",
"description": "Mnemoverse API key (starts with mk_live_), for this local package only: the hosted server https://mcp.mnemoverse.com/mcp signs in with OAuth and takes no key. Optional to install and inspect — the server starts and lists its tools without a key; every actual tool call requires one. Get one free in ~30s at https://console.mnemoverse.com",
"password": true
}
],
"servers": {
"mnemoverse": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@mnemoverse/mcp-memory-server@latest"
],
"env": {
"MNEMOVERSE_API_KEY": "${input:mnemoverse-api-key}",
"MNEMOVERSE_API_URL": "https://core.mnemoverse.com/api/v1"
}
}
}
}
Devin Desktop (formerly Windsurf) — add to ~/.config/devin/mcp_config.json:
{
"mcpServers": {
"mnemoverse": {
"command": "npx",
"args": [
"-y",
"@mnemoverse/mcp-memory-server@latest"
],
"env": {
"MNEMOVERSE_API_KEY": "mk_live_YOUR_KEY",
"MNEMOVERSE_API_URL": "https://core.mnemoverse.com/api/v1"
}
}
}
}
More MCP clients — same server, different config file:
Zed — add to ~/.config/zed/settings.json (Zed uses context_servers, and "source": "custom" is required):
{
"context_servers": {
"mnemoverse": {
"source": "custom",
"command": "npx",
"args": [
"-y",
"@mnemoverse/mcp-memory-server@latest"
],
"env": {
"MNEMOVERSE_API_KEY": "mk_live_YOUR_KEY",
"MNEMOVERSE_API_URL": "https://core.mnemoverse.com/api/v1"
}
}
}
}
JetBrains (AI Assistant) — Settings → Tools → AI Assistant → Model Context Protocol (MCP), then paste:
{
"mcpServers": {
"mnemoverse": {
"command": "npx",
"args": [
"-y",
"@mnemoverse/mcp-memory-server@latest"
],
"env": {
"MNEMOVERSE_API_KEY": "mk_live_YOUR_KEY",
"MNEMOVERSE_API_URL": "https://core.mnemoverse.com/api/v1"
}
}
}
}
Cline — MCP Servers → Configure (or edit cline_mcp_settings.json). Cline reads env values literally, so paste your real key — not a ${VAR} reference:
{
"mcpServers": {
"mnemoverse": {
"command": "npx",
"args": [
"-y",
"@mnemoverse/mcp-memory-server@latest"
],
"env": {
"MNEMOVERSE_API_KEY": "mk_live_YOUR_KEY",
"MNEMOVERSE_API_URL": "https://core.mnemoverse.com/api/v1"
}
}
}
}
Why
@latest? Barenpx @mnemoverse/mcp-memory-serveris cached indefinitely by npm and stops re-checking the registry. The@latestsuffix forces a metadata lookup on every Claude Code / Cursor / VS Code session start (~100-300ms), so you always pick up new releases.
⚠️ Restart your AI client after editing the config. MCP servers are only picked up on client startup.
Paste this in your AI chat:
"Remember that my favourite TypeScript framework is Hono, and please call
memory_writeto save it."
Your agent should call memory_write and confirm the memory was stored.
Then open a new chat / new session (this is the whole point — memory survives restarts), and ask:
"What's my favourite TypeScript framework?"
Your agent should call memory_read, find the entry, and answer "Hono". If it does — you're wired up. Write whatever you want next.
If it doesn't remember: check that the client was fully restarted and the config has your real mk_live_... key, not the placeholder. On the hosted server there is no key to check; check that the browser sign-in finished (in Cursor, Connect next to mnemoverse).
⭐ If the second session remembered, star the repo. It helps other builders find it.
The test above works because you asked the agent to call the tool. In normal work it will not, unless it has a standing instruction that says when to read memory and when to save. The setup_memory prompt writes those rules for Claude Code, Claude, Cursor or Codex, and Make Your Agent Use Memory explains where they go and how to confirm the tools work first.
Four named prompts for clients that show MCP prompts as commands (Claude Code as /mcp__mnemoverse__<name>). None of them calls the API itself: three ask the model to use the tools above, and setup_memory hands you rules for your own agent.
memory://item/{memory_id} opens one saved memory by its id (the id: line of a memory_read result) for clients that attach MCP resources. It returns the memory's memory_id, content and domain as JSON. It reads your own store only: a memory read from a shared room cannot be opened by id.
tools/list is frozen per released version, so a client can save the list it
saw and diff it against what the server serves today, by version.
annotations
object of every tool (title, readOnlyHint, destructiveHint,
idempotentHint, openWorldHint) do not change. Only text may: descriptions
and what a tool returns, as the CHANGELOG rules state.outputSchema, with
structuredContent returned alongside the same text) to a tool that did
not have one; once declared, that schema's fields are add-only under this
same rule. Where this server's output schema deliberately differs from the
hosted connector's, the CHANGELOG entry says so; today that is
memory_id in every output schema, a plain string here and a
GUID-validated string there (this package's ids are opaque);
memory_list_recent's next_cursor, optional here (absent when the
service sent a continuation token this client will not pass on) and
required there; memory_stats, which carries five optional fields
(episodes, prototypes, hebbian_edges, avg_valence,
avg_importance) the connector's schema does not declare; the room
tools (memory_create_room, memory_invite_to_room, memory_join_room,
memory_list_rooms), where several fields the connector marks required
are optional here (name, scope, already_member, and the invite's
code, scope, room_address and expires_at), because a value core
did not send is an honest outcome here rather than a placeholder; and
memory_list_rooms and vault_list, which drop a row with no usable
identity (room_id, address, role; alias, context) from the data,
reported once on stderr, instead of emitting empty strings into required
fields; and memory_read and memory_list_recent, which carry an optional
rooms_not_searched field (the shared rooms an unscoped call did not
search) that the connector's schemas do not declare yet.deprecated since x.y, removed in x.z, and the change lands only in the
announced version, with its CHANGELOG line. A renamed parameter is accepted
under both names until then (0.11 renamed memory_feedback's atom_ids to
memory_ids; the old name was removed in 0.13, as announced after 0.12
shipped sooner than the first announcement assumed). A rename is announced by naming
both the old and the new name; the version pair alone does not say what a
client should look for. Because a MINOR may add a field but not remove one, a
renamed annotation field is declared under both names until the announced
version.tools/list outputs. One exception, by configuration: a server
built on the /shared entry point may ask for its own noun in the three
descriptions that name the server (wording.serverNoun, below), which
changes those three description strings and nothing else; tool names,
input and output schemas and annotations never vary by configuration.Every inputSchema and outputSchema is JSON Schema 2020-12, the dialect MCP
assumes when a schema names none, and names none (#189).
The list above is the current surface: eleven tools, each declaring all four hints.
The hosted connector at mcp.mnemoverse.com/mcp serves the same surface, registered
from this package at the version it pins. The list itself is published as
tools.json, generated from the built server (name, title,
description and annotations per tool); the test suite and the release workflow
fail when it does not list what the server registers, and the .mcpb manifest's
tool list is derived from it.
If the hosted connector stops answering in a session. A client can keep showing the connector as connected while every call in that session fails with "not connected". Reconnecting it on claude.ai does not revive a session that is already stuck; reconnect from inside the session instead (in Claude Code, /mcp, then sign in again). Meanwhile this local server, set up with an API key from the same account as in the Quick Start, reaches the same memory and does not depend on that session's sign-in.
@mnemoverse/mcp-memory-server/shared is the entry point another server registers these same tools from, instead of keeping its own copy (ADR-025, mnemoverse-core). It exports registerMemoryTools/registerMemoryPrompts/registerMemoryResources, the three typed error classes (ApiError, NetworkError, UnreadableBodyError), MAX_RESULT_CHARS/capResult, and two optional dependencies a hosted deployment injects to speak in its own voice: wording (its own server noun and error vocabulary, including an OAuth mode under which no 401 or 403 explanation names an API key) and writeAuthor (vouching for the end user behind a write). See docs/shared.md for the full contract.
The pattern that pays off first is cross-tool continuity: a decision made while pairing in Claude Code is there when you open Cursor an hour later, and the preference you stated in VS Code holds in a ChatGPT session that evening. Teams use shared rooms the same way — one place where an agent's lessons about a codebase accumulate instead of being re-taught per seat. And rating a recalled memory as helpful or misleading re-ranks what comes back next, which matters once a store grows past what anyone curates by hand.
Concrete things worth writing:
The same API key works across all tools. Write a memory in Claude Code — read it in Cursor. Learn something in VS Code — your GPT Custom Action knows it too.
┌── Claude Code (this MCP server)
├── Cursor (this MCP server)
Mnemoverse API ──├── VS Code (this MCP server)
(one memory) ├── GPT (Custom Actions)
├── Python SDK (pip install mnemoverse)
└── REST API (curl)
The retrieval model is published: arXiv:2603.08965, accepted at the GRAAI workshop at IEEE WCCI 2026 — it establishes the abstraction-discovery method the memory model builds on. No benchmark figures appear in this README, ours or anyone's: numbers will come with a reproducible run to stand behind, not before.
Setup and reference
Background reading
Other ways to install it
The same memory, packaged for hosts that prefer a plugin or an extension over an MCP config block. How each one connects and authenticates differs, so the line below says which is which rather than claiming one flow for all of them.
agent-memory-discipline skill
claude plugin marketplace add mnemoverse/claude-plugin
claude plugin install mnemoverse@mnemoverse
gemini extensions install https://github.com/mnemoverse/gemini-extensionmanifest.json in this repository is an MCPB manifest. This one is different from the four above: it runs the server as a local node process and reads MNEMOVERSE_API_KEY from the extension settings rather than calling the hosted endpoint. The packaged .mcpb ships with each releaseStanding rules, separate from this server
.claude-plugin/.Project
This server sends to the Mnemoverse API (core.mnemoverse.com), authenticated with your API key, what a tool call carries — and nothing else it can see. It does not read your AI client's conversation history, your local files, or anything you don't pass to a memory_* / vault_* tool. Stored memories live under your account; Mnemoverse never sells them and never shares them on its own. The one sharing path is the one you create yourself: inviting someone to a shared room grants their assistant access to that room's memories, bounded by the invite's scope.
What each tool sends:
One thing goes out that you did not explicitly request: since 0.8.1, when a search or feed comes back empty, the server sends one or two authenticated read-only GET probes (/memory/rooms and/or /memory/stats) so the empty answer can say what it did not cover. Since 0.16.0 a search or feed without domain that does return results also sends one, to /memory/rooms, so the answer can name the shared rooms it did not search. The probes carry your API key and nothing else, change no stored state, and are disclosed in the CHANGELOG.
MIT © Mnemoverse
Hosted persistent memory for AI agents over MCP. Tell it a recalled memory helped or misled, and it re-ranks what comes back next. Shared rooms for multi-agent work. One key or OAuth across Claude Cod
{ "mcpServers": { "mnemoverse-mcp-memory-server-github": { "url": "https://mcp.mnemoverse.com/mcp", "headers": {} } }}ภาพรวม
Hosted persistent memory for AI agents over MCP. Tell it a recalled memory helped or misled, and it re-ranks what comes back next. Shared rooms for multi-agent work. One key or OAuth across Claude Code, Cursor, VS Code and ChatGPT. MIT, in the official MCP Registry.
เครื่องมือ
ยังไม่มีรายการเครื่องมือ เซิร์ฟเวอร์แบบรีโมตจะได้รายการหลังการตรวจสอบสถานะครั้งแรก
FAQ
คัดลอกคอนฟิก http สำหรับ Cursor, Claude Desktop, Claude Code หรือ VS Code ได้ในหน้านี้ คอนฟิกนี้ใช้การติดตั้งของผู้เผยแพร่ ไม่ใช่พร็อกซีของ PlugMCP
ผู้เผยแพร่ระบุตัวแปรสภาพแวดล้อมเหล่านี้: MNEMOVERSE_API_KEY, MNEMOVERSE_API_URL
MCP Memory Server เข้าถึงได้ผ่าน HTTP
ตรวจสอบล่าสุดเมื่อ 2026-11-12 Hosted persistent memory for AI agents over MCP. Tell it a recalled memory helped or misled, and it re-ranks what comes back next. Shared rooms for multi-agent work. One key or OAuth across Claude Code, Cursor, VS Code and ChatGPT. MIT, in the official MCP Registry.