Turbo Quant Memory

Name: Turbo Quant Memory
Author: Lexus2016

by Lexus2016version 0.36.1i★ 10iRuns on your computer

Registry nameio.github.Lexus2016/turbo-quant-memory

How to install

What it does

Local-first memory and knowledge graph for coding agents. Compact retrieval, no network.

Connects Runs on your computer
Account or key Needs TQMEMORY_SECRETS_PASSPHRASE
Category Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Passed 3/3 checks · Runs on your computer · ✓ Commands checked Nov 14, 2026

First: which AI do you use?

ClaudeWeb · app · phoneChatGPTWebClaude CodeTerminalCursorCode editorVS CodeCode editorOtherOther apps

Pick your app and the steps appear below.

Works with Claude, with some setup first

You need a Turbo Quant Memory key (create it on the maker’s site) · Install Python (uv) on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone

Install Python (uv)
One time only; it works for every server that needs Python (uv)
Open the Python (uv) download page ↗
Done
Sign up and create a Turbo Quant Memory key
Open the maker’s site, sign up and create an API key for the next step. Check the maker’s site for pricing and free plans.
Open the Turbo Quant Memory site ↗
Done
Open the Claude desktop app’s settings file
SettingsDeveloperEdit Config
Done

Paste these settings and save the file

{
  "mcpServers": {
    "turbo-quant-memory": {
      "command": "uvx",
      "args": [
        "turbo-quant-memory",
        "serve"
      ],
      "env": {
        "TQMEMORY_SECRETS_PASSPHRASE": "your-value"
      }
    }
  }
}

Paste the key only into the app’s field, never into a chat or to anyone

Done

Quit Claude and open it again
Done
Try it
Use Turbo Quant Memory and tell me what you can do for me, then show me one thing
✓ If Claude says it is using Turbo Quant Memory or shows a Turbo Quant Memory tool in the answer, you are connected

3 optional setting(s) (works without them)

The command above works without these. Add them only if you want to change something, following the maker’s description (original English).

TQMEMORY_FTS_LANGUAGE Snowball stemmer for the BM25 lane. Use Russian for Cyrillic-dominant corpora. · default English
TQMEMORY_EMBEDDING_BACKEND Embedder backend. Default fastembed (ONNX); sentence-transformers needs the [torch] extra. · default fastembed
TQMEMORY_MIGRATE_ON_STARTUP Set to 1 to apply pending schema migrations automatically on startup. · default 0

Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version

ChatGPT cannot connect Turbo Quant Memory yet

Turbo Quant Memory runs on your computer, but ChatGPT can only connect servers that run on the web

What you can do instead

A · Use an app that can connect Turbo Quant Memory

Steps for Claude →You need a Turbo Quant Memory key (create it on the maker’s site) · Install Python (uv) on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone
Steps for Claude Code →You need a Turbo Quant Memory key (create it on the maker’s site) · Install Python (uv) on your computer first (one time)
Steps for Cursor →You need a Turbo Quant Memory key (create it on the maker’s site) · Install Python (uv) on your computer first (one time)
Steps for VS Code →You need a Turbo Quant Memory key (create it on the maker’s site) · Install Python (uv) on your computer first (one time)

B · Others in Search & AI memory that work with ChatGPT

Picked from the most used in the same category, only ones that connect by address with no key

Context7✓ ChatGPT
OpenSEO✓ ChatGPT
AIHOT✓ ChatGPT

Works with Claude Code, with some setup first

You need a Turbo Quant Memory key (create it on the maker’s site) · Install Python (uv) on your computer first (one time)

Install Python (uv)
One time only; it works for every server that needs Python (uv)
Open the Python (uv) download page ↗
Done
Sign up and create a Turbo Quant Memory key
Open the maker’s site, sign up and create an API key for the next step. Check the maker’s site for pricing and free plans.
Open the Turbo Quant Memory site ↗
Done
Open Terminal
Mac: press Command+Space and type Terminal · Windows: open PowerShell
Done
4
Paste this command and press Enter
```
claude mcp add --scope user turbo-quant-memory --env TQMEMORY_SECRETS_PASSPHRASE=your-value -- uvx turbo-quant-memory serve
```
Replace “your-value” with your key before pressing Enter
Paste the key only into the app’s field, never into a chat or to anyone
Done
Type /mcp in Claude Code
You should see Turbo Quant Memory listed as connected
Done
Try it
Use Turbo Quant Memory and tell me what you can do for me, then show me one thing
✓ If Claude Code says it is using Turbo Quant Memory or shows a Turbo Quant Memory tool in the answer, you are connected

3 optional setting(s) (works without them)

The command above works without these. Add them only if you want to change something, following the maker’s description (original English).

TQMEMORY_FTS_LANGUAGE Snowball stemmer for the BM25 lane. Use Russian for Cyrillic-dominant corpora. · default English
TQMEMORY_EMBEDDING_BACKEND Embedder backend. Default fastembed (ONNX); sentence-transformers needs the [torch] extra. · default fastembed
TQMEMORY_MIGRATE_ON_STARTUP Set to 1 to apply pending schema migrations automatically on startup. · default 0

Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Works with Cursor, with some setup first

You need a Turbo Quant Memory key (create it on the maker’s site) · Install Python (uv) on your computer first (one time)

Install Python (uv)
One time only; it works for every server that needs Python (uv)
Open the Python (uv) download page ↗
Done
Sign up and create a Turbo Quant Memory key
Open the maker’s site, sign up and create an API key for the next step. Check the maker’s site for pricing and free plans.
Open the Turbo Quant Memory site ↗
Done
Click this button to open Cursor
Open in Cursor
Cursor asks you to confirm; click Install
Done
Fill in your key
In the Turbo Quant Memory settings, TQMEMORY_SECRETS_PASSPHRASE is empty; add your key and save
Paste the key only into the app’s field, never into a chat or to anyone
Done
Open the AI chat in Cursor in Agent mode
Done
Try it
Use Turbo Quant Memory and tell me what you can do for me, then show me one thing
✓ If Cursor says it is using Turbo Quant Memory or shows a Turbo Quant Memory tool in the answer, you are connected

3 optional setting(s) (works without them)

The command above works without these. Add them only if you want to change something, following the maker’s description (original English).

TQMEMORY_FTS_LANGUAGE Snowball stemmer for the BM25 lane. Use Russian for Cyrillic-dominant corpora. · default English
TQMEMORY_EMBEDDING_BACKEND Embedder backend. Default fastembed (ONNX); sentence-transformers needs the [torch] extra. · default fastembed
TQMEMORY_MIGRATE_ON_STARTUP Set to 1 to apply pending schema migrations automatically on startup. · default 0

Menu names checked against Cursor’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Works with VS Code, with some setup first

You need a Turbo Quant Memory key (create it on the maker’s site) · Install Python (uv) on your computer first (one time)

Install Python (uv)
One time only; it works for every server that needs Python (uv)
Open the Python (uv) download page ↗
Done
Sign up and create a Turbo Quant Memory key
Open the maker’s site, sign up and create an API key for the next step. Check the maker’s site for pricing and free plans.
Open the Turbo Quant Memory site ↗
Done
Click this button to open VS Code
Open in VS Code
VS Code asks you to confirm; click Install
Done
Fill in your key
In the Turbo Quant Memory settings, TQMEMORY_SECRETS_PASSPHRASE is empty; add your key and save
Paste the key only into the app’s field, never into a chat or to anyone
Done
Open the AI chat in VS Code in Agent mode
Done
Try it
Use Turbo Quant Memory and tell me what you can do for me, then show me one thing
✓ If VS Code says it is using Turbo Quant Memory or shows a Turbo Quant Memory tool in the answer, you are connected

3 optional setting(s) (works without them)

The command above works without these. Add them only if you want to change something, following the maker’s description (original English).

TQMEMORY_FTS_LANGUAGE Snowball stemmer for the BM25 lane. Use Russian for Cyrillic-dominant corpora. · default English
TQMEMORY_EMBEDDING_BACKEND Embedder backend. Default fastembed (ONNX); sentence-transformers needs the [torch] extra. · default fastembed
TQMEMORY_MIGRATE_ON_STARTUP Set to 1 to apply pending schema migrations automatically on startup. · default 0

Menu names checked against VS Code’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Other apps that use MCP, such as Windsurf, Zed or Gemini CLI, each add servers differently. See how in the app list.

See every app that uses MCP →

JSON settings are under “For developers” below

Stuck? Ask people who use Turbo Quant Memory💬 Discussion →

For developers: Terminal commands and JSON settings

Installed on your computer

Claude Code

claude mcp add --scope user turbo-quant-memory --env TQMEMORY_SECRETS_PASSPHRASE=your-value -- uvx turbo-quant-memory serve

Claude Desktop (claude_desktop_config.json)

{
  "mcpServers": {
    "turbo-quant-memory": {
      "command": "uvx",
      "args": [
        "turbo-quant-memory",
        "serve"
      ],
      "env": {
        "TQMEMORY_SECRETS_PASSPHRASE": "your-value"
      }
    }
  }
}

Cursor (~/.cursor/mcp.json)

{
  "mcpServers": {
    "turbo-quant-memory": {
      "command": "uvx",
      "args": [
        "turbo-quant-memory",
        "serve"
      ],
      "env": {
        "TQMEMORY_SECRETS_PASSPHRASE": "your-value"
      }
    }
  }
}

VS Code (mcp.json)

{
  "servers": {
    "turbo-quant-memory": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "turbo-quant-memory",
        "serve"
      ],
      "env": {
        "TQMEMORY_SECRETS_PASSPHRASE": "your-value"
      }
    }
  }
}

Values you fill in

TQMEMORY_FTS_LANGUAGE env
Snowball stemmer for the BM25 lane. Use Russian for Cyrillic-dominant corpora.
TQMEMORY_EMBEDDING_BACKEND env
Embedder backend. Default fastembed (ONNX); sentence-transformers needs the [torch] extra.
TQMEMORY_MIGRATE_ON_STARTUP env
Set to 1 to apply pending schema migrations automatically on startup.
TQMEMORY_SECRETS_PASSPHRASE secret required env
Argon2id passphrase for the secrets vault on headless hosts. Omit to use the OS keyring.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

At a glance

GitHub stars i: 10
Downloads per weeki: 54/wk
Licence i: MIT
Connection: Runs on your computer
Transport: stdio
Latest versioni: 0.36.1
Categoryi: Search & AI memory
Published to registryi: Nov 9, 2026
Code last changedi: Nov 10, 2026
Maker: Lexus2016
Packages: pypi: turbo-quant-memory
Repo: Lexus2016/turbo_quant_memory
Website: github.com
Registry status: Active

Which apps can use it

Based on how this server connects and on each app’s own docs, checked Nov 10, 2026.

Run on your computer in

Claude Goose LM Studio Msty Studio Cherry Studio Cursor VS Code + GitHub Copilot Visual Studio Windsurf (Devin Desktop)Zed Kiro Cline Continue JetBrains AI Assistant Claude Code Codex CLI Gemini CLI OpenCode nodecode Warp LibreChat Raycast

All apps, with pros and cons →

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 14, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account Lexus2016, which owns the repo
✓ Pass
Still maintained
Code last changed 4 days ago
✓ Pass
Has a licence
Uses MIT
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Discussion

Ask, share a tip or report that it does not work. Sorted by what people marked helpful.

No posts yet. Be the first to ask or share.

Posts here are written by users, not the PopNx team.

User reviews

No reviews yet

Compared with others in Search & AI memoryi

More stars than 92% of the other 6081 servers in this category
Published to the registry more recently than 89% of the other 6081 servers in this category
Basic checks equal to or better than 100% of the other 6081 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Turbo Quant Memory safe?

It passed 3 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: TQMEMORY_SECRETS_PASSPHRASE

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed 4 days ago, and the latest version (0.36.1) reached the registry 5 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, OpenSEO

Others in the same category

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

by upstashWidely used↓ 1.2M/wk★ 64.8KUpdated 2 days ago

Computer or cloud

Install

Codebase Memory

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

by DeusDataWidely used↓ 16.8K/wk★ 48.6KUpdated 28 days ago

Runs on your computer

Install

OpenSEO

Keyword research, site audits, rank tracking and AI visibility for your AI agent.

by every-appWidely used★ 27.6KUpdated today

Runs in the cloud✓ everyapp.com

How to connect

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Local-first memory and knowledge graph for AI coding agents

Your agent stops re-reading files and re-deriving the same conclusions.

Your notes, code and secrets never leave your machine.

Demo

Watch the 30-second demo

The problem

A long session accumulates hard-won detail about why the code is the way it is. Then the context compacts and it is gone. Next session the agent re-reads the same files, re-derives the same conclusions, and bills you for the same tokens again.

CLAUDE.md does not scale past a few dozen lines, and it cannot answer *"what did we decide about X, and why?"*.

Turbo Quant Memory is an MCP server that gives the agent a persistent, searchable store it writes to while it works — decisions, lessons, patterns, session handoffs — plus a compact index of your Markdown. Retrieval returns ~220-character result cards rather than whole documents; the agent loads full content only when a card is not enough.

Why this one

	Turbo Quant Memory	mem0 / OpenMemory	MCP `memory` server
Where your data lives	your disk, always	vendor cloud or self-host	your disk
Your data leaves the host	never	yes, unless self-hosted	never
Retrieval	hybrid BM25 + dense vector, RRF-fused	dense vector	exact graph lookup
What a search returns	compact cards, hydrate on demand	full memories	full nodes
Knowledge graph	yes — with lifecycle + linting	no	yes
Non-English content	Cyrillic exact-match out of the box	varies	n/a
Measures its own savings	yes — `server_info()`	no	no
Price	free, MIT	paid tiers	free

No HTTP client, no telemetry, no phone-home. Verify it yourself — this returns nothing:

grep -rnE '^[[:space:]]*(import|from)[[:space:]]+(requests|httpx|aiohttp|urllib3)\b' src/

To be precise about the one exception: on first run fastembed downloads the embedding model (~0.22 GB) from Hugging Face. After that the server runs fully offline. Your notes, code and secrets are never transmitted anywhere — there is nothing in the package that could send them.

Install

Let your agent install it

Paste this into Claude Code, Codex, Gemini CLI, Cursor or Antigravity:

Install and configure the Turbo Quant Memory MCP server for this workspace from

https://github.com/Lexus2016/turbo_quant_memory — follow the README, register the

tqmemory server, run turbo-memory-mcp skill install, run the health check, and

index this project.

skill install copies an operating manual into every agent skill directory on the machine, so every future session already knows how to use the memory without being told.

Or install it yourself

uv tool install turbo-quant-memory

Upgrading from 0.27.x or earlier? The distribution was renamed in 0.28.0, so uv tool upgrade turbo-memory-mcp no longer resolves — run uv tool install --force turbo-quant-memory once, and uv tool upgrade turbo-quant-memory afterwards. The turbo-memory-mcp command itself is unchanged, so client configs keep working.

Then register the server with your client:

claude mcp add --scope project tqmemory -- turbo-memory-mcp serve   # Claude Code

codex mcp add tqmemory -- turbo-memory-mcp serve # Codex gemini mcp add tqmemory turbo-memory-mcp serve # Gemini CLI

Cursor, OpenCode, Antigravity and other clients → CLIENT_INTEGRATIONS.md. Hermes runs MCP through a systemd gateway → docs/hermes.md.

📈 It measures its own savings — see for yourself

Turbo Quant Memory doesn't just *claim* to save tokens — every install keeps a running tally you can read anytime with server_info() (field usage_stats.headline). The savings are yours to verify, not ours to promise.

Live snapshot from a real developer instance (v0.28.2):

What the memory did	Number
🔢 Input tokens saved (cumulative)	≈ 2,640,000 and counting
🔁 Retrievals served	2,280 searches + 280 deep hydrations
📉 Average saved per retrieval	≈ 1,200 tokens
📚 Knowledge under management	237 active notes + 763 indexed code blocks
🛡️ Integrity	0 corrupted records · 0 pending migrations

These are one machine's cumulative numbers, not a synthetic benchmark — your own counter starts at zero and grows as your agent works. Run server_info() on your install to see your real figure.

What it does

Typed notes. decision, lesson, pattern, handoff — each stored with tags, provenance and a knowledge-graph link to the file or issue it is about.
Tiered memory. durable (decisions, patterns) and reference (indexed docs) are searched by default; episodic (session handoffs) stays out of the way until you ask for it, so yesterday's noise never buries an architectural decision.
Hybrid retrieval. A dense vector lane leads; a BM25 lane rescues exact terms — function names, file paths, IDs — fused with Reciprocal Rank Fusion. Cyrillic and other non-English terms match exactly, case- and accent-insensitive, with no configuration.
Knowledge graph. Directed, timestamped relations between notes, files and issues. Search results carry the linked context inline, so the agent does not need a second lookup.
Human notes outrank agent notes. Anything you explicitly asked to remember is flagged human-explicit and ranks above the agent's own observations at equal relevance.
Encrypted secrets vault. Project-scoped, AES-256-GCM, structurally unreachable from search. → docs/secrets-vault.md
Runs on a small machine. The default embedder is ONNX via fastembed — no PyTorch, ~0.22 GB model, comfortable on 2 GB of RAM.
Several agents, one project — automatically. Agents working in the same git working tree see each other's sessions, announced work and recent file changes; while two or more of them share the tree, changes to text files are recorded so they can be restored. No setup.

Full technical detail → docs/features.md

Several agents in one project

If you run more than one agent in the same working tree, tqmemory connects them automatically. There is nothing to configure.

Agents see each other. workspace_status lists the active sessions, what each one announced it is working on (announce_work, finish_work) and which files changed recently. A session that made no tqmemory call for 30 minutes is listed under idle_sessions instead: it is not an active peer and its announced areas are left out of overlaps. Other tqmemory responses carry a short workspace note only when something new has happened, and never for a lone session. health and server_info always include a workspace diagnostics block.
Changes are recorded. While two or more sessions share a git working tree, the watcher records new versions of text files it sees change (up to 1 MiB each, skipping anything matched by .gitignore or .tqmemoryignore). Several quick writes in a row can be merged into one version. file_history lists the versions and restore_file brings one back; the restore is itself undoable. The same is available from a terminal: turbo-memory-mcp files log and turbo-memory-mcp files restore.
Limits. Versions are recorded only while two or more sessions share a git working tree. The journal never runs outside a git working tree, in your home directory or at a filesystem root. Defaults: 1 MiB per file, a 256 MiB per-project size target and 14 days of retention. Recorded versions stay recoverable for 14 days; past that, or when the project is over its size target, the oldest are removed. The newest version of each file changed in the last 24 hours is never dropped for size. These defaults are set by TQMEMORY_JOURNAL_MAX_FILE_BYTES, TQMEMORY_JOURNAL_MAX_BYTES and TQMEMORY_JOURNAL_RETENTION_DAYS; the size limit is a target, not a hard maximum.

This is partial protection, not a guarantee that every change is saved. It does not block writes: two agents can still overwrite each other's work, and tqmemory can only show it and help you recover. Agents that never call tqmemory see nothing. It works on one computer only. To turn it off, set TQMEMORY_WORKSPACE_DISABLE=1.

The 24 MCP tools

Group	Tools
Write	`remember_note` · `deprecate_note` · `promote_note` · `index_paths`
Read	`semantic_search` · `hydrate` · `recent_context` · `list_scopes`
Graph	`link_entities` · `unlink_entities` · `get_related_entities`
Hygiene	`lint_knowledge_base` · `health` · `self_test` · `server_info`
Vault	`set_secret` · `get_secret` · `list_secrets` · `delete_secret`
Workspace	`announce_work` · `finish_work` · `workspace_status` · `file_history` · `restore_file`

Documentation


MEMORY_STRATEGY.md	How to actually use the memory day to day
CLIENT_INTEGRATIONS.md	Per-client setup: Cursor, OpenCode, Antigravity, …
TECHNICAL_SPEC.md	Architecture and storage format

| [docs/featur

Only the beginning is shown; read the rest in the repo

Turbo Quant Memory

What it does

Install

Install Python (uv)

Sign up and create a Turbo Quant Memory key

Open the Claude desktop app’s settings file

Paste these settings and save the file

Quit Claude and open it again

Try it

What you can do instead

Install Python (uv)

Sign up and create a Turbo Quant Memory key

Open Terminal

Paste this command and press Enter

Type /mcp in Claude Code

Try it

Install Python (uv)

Sign up and create a Turbo Quant Memory key

Click this button to open Cursor

Fill in your key

Open the AI chat in Cursor in Agent mode

Try it

Install Python (uv)

Sign up and create a Turbo Quant Memory key

Click this button to open VS Code

Fill in your key

Open the AI chat in VS Code in Agent mode

Try it

Installed on your computer

Values you fill in

At a glance

Which apps can use it

Related guides

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Discussion

User reviews

Compared with others in Search & AI memoryi

Common questions

Others in the same category

Context7

Codebase Memory

OpenSEO

README from the maker

Demo

The problem

Why this one

Install

Let your agent install it

Or install it yourself

📈 It measures its own savings — see for yourself

What it does

Several agents in one project

The 24 MCP tools

Documentation