G
goyohan0611-png/graph-mind
Local long-term memory for AI agents. Keeps every conversation word for word, costs nothing to save, and is shared by all your agents. Beat Mem0, MemPalace and agentmemory on the same tests.
SECURITY.md ✓
View on GitHub ↗Link checked 2026-11-12 · HTTP 200 · redirects to github.com
Install & config
- Copy the command above
- Paste it as one entry under
mcpServersinclaude_desktop_config.json— local servers take command + args (example: clients) - Restart your client
Install command from the repository
pip install graph-mind-memory
Parsed from the README we fetched on 2026-10-26; we have not executed it.
This is the install method the repository states, not an MCP client config, so no JSON is generated.
Key names differ by client: Clients & CLI
- Star count
- 8 ★ · goyohan0611-png/graph-mind · read from the repository page · (checked 2026-11-13 20:00:50)
- Source
- collected from the punkpeye/awesome-mcp-servers list · type: MCP server
- Harvest history
- first seen 2026-10-23 · last seen 2026-11-14 · seen 26× · listed by 23 sources
- Score
- score 2,300 · 8 ★ · 23 sources · mcp
- Install
pip install graph-mind-memory
FAQ (answers come from our records)
How do I install it?
The repository provides this install command:
pip install graph-mind-memory. It comes from the repository itself; we cannot guarantee it runs as-is in your client.Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository
goyohan0611-png/graph-mind;first catalogued 2026-10-23;last seen 2026-11-14。There is no official certification or quality rating here — we record sources and dates only.# Graph-MIND
以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →
### Your AI forgets everything when the session ends. This one remembers, and it never calls an LLM to do it.
88.8% on LongMemEval. Zero model tokens spent saving memory. Runs on your own PC.
[![][license-shield]][license-link]
[![][python-shield]][python-link]
[![][platform-shield]][platform-link]
[![][longmemeval-shield]][benchmarks-link]
[![][ci-shield]][ci-link]
[![][pypi-shield]][pypi-link]
Decide something with one agent on Monday. Ask another on Wednesday. It knows.
English · 한국어
Recorded live on one PC: Claude Code (Opus 5.5, effort high) and Codex (GPT-6.1-Sol, effort high) sharing one Graph-MIND memory. Model thinking time is fast-forwarded.
## Install
Windows: download Graph-MIND-Setup.cmd
and double-click it, or in PowerShell:
powershell
irm https://raw.githubusercontent.com/goyohan0611-png/graph-mind/main/scripts/install.ps1 | iex
macOS / Linux:
bash
curl -LsSf https://raw.githubusercontent.com/goyohan0611-png/graph-mind/main/scripts/install.sh | sh
No Python needed; nothing else to set up. Restart your AI apps afterwards. Already have Python?
pip install graph-mind-memory && graph-mind-install. More: docs/install.md.
Connecting an MCP client by hand
After pip install graph-mind-memory:
json
"mcpServers": {
"graph-mind-memory": {
"command": "python",
"args": ["-m", "graphmind.mcpserver"]
Claude Code: claude mcp add graph-mind-memory -- python -m graphmind.mcpserver. This gives the
tools only; graph-mind-install also saves every conversation automatically.
## Try it
Work as usual for a while, then open a new session, another app, or another model and ask:
"Where did we leave off yesterday?"
"Which database did we pick for the billing service, and why?"
"What did you change in the auth middleware last week?"
"What's my dog's name?" (any fact you mentioned once, in passing)
Nothing to tag or save by hand: every turn is already stored, and the agent pulls back the few
that answer the question.
## What it does
One shared brain for every agent in your terminal. Whichever coding agent or model you
run, they all read and write the same memory. Switch agents or models; the memory stays.
Remembers conversations word for word, on your own PC. Saving is a database write: no model
call, no tokens. When a question depends on the past, the agent gets back the few thousand
tokens that answer it. Korean and English.
One memory across your PCs. Run graph-mind folder share, then graph-mind folder on
the other PC (the AI tells you the command; it never moves your memory by itself, so a web page
cannot either). Office network or Tailscale, over TLS, every line
encrypted before it leaves a PC.
Hand a memory to someone else as a file. graph-mind export FILE writes all of it;
--project FOLDER writes only the conversations held in that folder. They run
graph-mind import FILE.
Yours. No account, no cloud of its own, no telemetry. Secrets are masked before anything is
stored, and "delete the password I typed earlier" deletes it everywhere. docs/privacy.md
Teams, if you want them. Share a project's decisions and progress with teammates' AIs, never
your personal memory; files stay in Slack and GitHub. docs/teams.md
## Works with
The installer finds these and connects them; run it again after installing a new one.
88.8% on LongMemEval. Zero model tokens spent saving memory. Runs on your own PC.
[![][license-shield]][license-link]
[![][python-shield]][python-link]
[![][platform-shield]][platform-link]
[![][longmemeval-shield]][benchmarks-link]
[![][ci-shield]][ci-link]
[![][pypi-shield]][pypi-link]
Decide something with one agent on Monday. Ask another on Wednesday. It knows.
English · 한국어
Recorded live on one PC: Claude Code (Opus 5.5, effort high) and Codex (GPT-6.1-Sol, effort high) sharing one Graph-MIND memory. Model thinking time is fast-forwarded.
## Install
Windows: download Graph-MIND-Setup.cmd
and double-click it, or in PowerShell:
powershell
irm https://raw.githubusercontent.com/goyohan0611-png/graph-mind/main/scripts/install.ps1 | iex
macOS / Linux:
bash
curl -LsSf https://raw.githubusercontent.com/goyohan0611-png/graph-mind/main/scripts/install.sh | sh
No Python needed; nothing else to set up. Restart your AI apps afterwards. Already have Python?
pip install graph-mind-memory && graph-mind-install. More: docs/install.md.
Connecting an MCP client by hand
After pip install graph-mind-memory:
json
"mcpServers": {
"graph-mind-memory": {
"command": "python",
"args": ["-m", "graphmind.mcpserver"]
Claude Code: claude mcp add graph-mind-memory -- python -m graphmind.mcpserver. This gives the
tools only; graph-mind-install also saves every conversation automatically.
## Try it
Work as usual for a while, then open a new session, another app, or another model and ask:
"Where did we leave off yesterday?"
"Which database did we pick for the billing service, and why?"
"What did you change in the auth middleware last week?"
"What's my dog's name?" (any fact you mentioned once, in passing)
Nothing to tag or save by hand: every turn is already stored, and the agent pulls back the few
that answer the question.
## What it does
One shared brain for every agent in your terminal. Whichever coding agent or model you
run, they all read and write the same memory. Switch agents or models; the memory stays.
Remembers conversations word for word, on your own PC. Saving is a database write: no model
call, no tokens. When a question depends on the past, the agent gets back the few thousand
tokens that answer it. Korean and English.
One memory across your PCs. Run graph-mind folder share, then graph-mind folder on
the other PC (the AI tells you the command; it never moves your memory by itself, so a web page
cannot either). Office network or Tailscale, over TLS, every line
encrypted before it leaves a PC.
Hand a memory to someone else as a file. graph-mind export FILE writes all of it;
--project FOLDER writes only the conversations held in that folder. They run
graph-mind import FILE.
Yours. No account, no cloud of its own, no telemetry. Secrets are masked before anything is
stored, and "delete the password I typed earlier" deletes it everywhere. docs/privacy.md
Teams, if you want them. Share a project's decisions and progress with teammates' AIs, never
your personal memory; files stay in Slack and GitHub. docs/teams.md
## Works with
The installer finds these and connects them; run it again after installing a new one.
Listed badge (optional)
Copy this line into the README if you want the listing mark. Optional, and it does not affect being listed.
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- Source
- awesome · https://github.com/goyohan0611-png/graph-mind
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