turbo_quant_memory

MCP server · PyPI · ★ 9 · graded 2026-10-24Source linked

Local-first MCP memory server for AI coding agents with compact retrieval and project/global scopes.

No outside reports on file

turbo_quant_memory is distributed via PyPI (turbo-quant-memory); review its source code, dependencies, and requested permissions before use.

Based on public adoption and transparency signals as of Oct 24, 2026. Our opinion, not a code audit or security guarantee.

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What it can access

Local filesNo local folder access notedLOW
Command executionRuns shell or system commandsREVIEW
Network reachConnects to outside service APINOTED
CredentialsNo API token requiredLOW
Package sourcePyPI (turbo-quant-memory)PUBLIC

Inferred from this listing’s public package details and description. Check the project’s source before installing.

Install

uvx turbo-quant-memory

All setup options ↓

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Everything known

We found nothing about this project in the sources we read (last checked 2026-10-30). That does not mean it has no problems.

0 incidents · 0 advisories · 0 news articles · 0 community threads · checked 2026-10-30

Popularity grade: C (from public signals such as stars and downloads, not a code review). Graded 2026-10-24.

Sources we read: OSV, GitHub Advisory Database, CISA Known Exploited Vulnerabilities, 44 security news feeds and our incident library. Last checked 2026-10-30.

Check a specific version →

About Turbo Quant Memory

Turbo Quant Memory is an MCP server focused on Cloud & infrastructure and Memory & knowledge: Local-first MCP memory server for AI coding agents with compact retrieval and project/global scopes.

It is published on PyPI as turbo-quant-memory and hosted on GitHub at Lexus2016/turbo_quant_memory (9 GitHub stars, 659 PyPI downloads). Based on its public metadata, it operates with standard local or API scope without broad shell execution flags noted.

Setup

Check these steps against the project’s own instructions before running anything.

Run the PyPI package turbo-quant-memory in an isolated environment:

bash

uvx turbo-quant-memory

See https://github.com/Lexus2016/turbo_quant_memory (opens external site) for required environment variables.

Why this grade

CC — Moderate risk signals

Signal-based grade (2/7 points): listed in several sources, public source code. This reflects adoption and transparency, not a code review.

Popularity and upkeep

35/100

GitHub stars: 9
PyPI downloads: 659
Listing last refreshed: 2026-10-29

These are public popularity signals, not a maintenance check. Look at the repository’s commit history and open issues.

Risks to watch for

Dependency & version pinning: Distributed via PyPI (turbo-quant-memory). Pin an exact release version or commit SHA rather than floating tags so upstream updates are reviewed first.

How to lower the risk

Least-privilege permissions

Give it access only to the specific folders, accounts or projects it needs, never your whole drive or admin account.
Use a separate, limited API key or login just for this tool so you can switch it off without affecting anything else.

Network isolation

Run it on a work computer or sandbox account, not one holding personal or company-sensitive data.
If your IT team can, limit which websites and services it is allowed to contact.

Monitoring

Check its activity history or logs weekly at first, and look at what it changed or sent.
Turn on alerts for new logins or unusual usage on any account it connects to.

Red flags to watch for

It asks for more access than its job requires, or prompts you to paste passwords.
It suddenly updates with new owners, or starts contacting unfamiliar websites.

Questions

How do I install Turbo Quant Memory?

Run uvx turbo-quant-memory (or pip install turbo-quant-memory) in your terminal, or add the server entry to your claude_desktop_config.json or .cursor/mcp.json as shown in the Setup section on this page. Full setup docs and environment variables are in github.com/Lexus2016/turbo_quant_memory.

Are there security reports about Turbo Quant Memory?

No reports found for this package in our research (last checked 2026-10-30). Turbo Quant Memory currently holds Grade C (Moderate risk signals) based on public adoption and transparency signals. Key risk areas to watch include dependency & version pinning:.

Is Turbo Quant Memory actively maintained?

Turbo Quant Memory has 9 GitHub stars and 659 PyPI downloads. Our directory data was last refreshed on 2026-10-29. Check recent commit activity, release tags, and open issues at github.com/Lexus2016/turbo_quant_memory before pinning it in production.

What are alternatives to Turbo Quant Memory?

You can compare Turbo Quant Memory side by side with other Memory MCP servers in the Related tools section on this page, or use the Compare tool on AgentArmorHQ.

Maintain or use Turbo Quant Memory? Show its live grade in your GitHub README, docs site, or run a check from the terminal before you install.

AgentArmorHQ Risk Grade C for Turbo Quant Memory

GitHub README Markdown:

markdown

[![AgentArmorHQ Risk Grade for Turbo Quant Memory](https://agentarmorhq.com/api/badge/lexus2016-turbo-quant-memory)](https://agentarmorhq.com/skills/lexus2016-turbo-quant-memory)

HTML embed:

html

<a href="https://agentarmorhq.com/skills/lexus2016-turbo-quant-memory"><img src="https://agentarmorhq.com/api/badge/lexus2016-turbo-quant-memory" alt="AgentArmorHQ Risk Grade for Turbo Quant Memory" height="20" /></a>

Terminal check:

terminal

curl -fsSL https://agentarmorhq.com/api/cli | node --input-type=module - check "lexus2016-turbo-quant-memory"

Share with your security lead

Need sign-off to use turbo_quant_memory? Copy this note for Slack, a ticket or a pull request.

### AgentArmorHQ Security Review Memo: turbo_quant_memory
- **Listing URL:** https://agentarmorhq.com/skills/lexus2016-turbo-quant-memory
- **Type:** App connector
- **Risk Grade:** Grade C (Moderate risk signals)
- **Outside Security Advisories on File:** 0
- **Public Adoption:** 9 GitHub stars

#### Permission & Blast-Radius Signals
- **Local files:** No local folder access noted
- **Command execution:** Runs shell or system commands
- **Network reach:** Connects to outside service API
- **Credentials:** No API token required
- **Package source:** PyPI (turbo-quant-memory)

#### Recommended Hardened Setup
- **Command:** `uvx turbo-quant-memory`
- **Controls:** Pin an exact version in `.mcp.json`, scope access to a single workspace folder, and use a least-privilege read-only token where supported.

_Based on public adoption and transparency signals as of Oct 24, 2026. Our opinion, not a code audit or security guarantee._

Key facts

Type: App connector
Publisher: Lexus2016
Source code: github.com/Lexus2016/turbo_quant_memory
Install command: pip install turbo-quant-memory
Est. context load: ~550 tokens / turn (~3 tool schemas, 0.27% of 200k context)
Popularity: 9 GitHub stars, 659 PyPI downloads
Last updated: 2026-10-29
Last graded: 2026-10-24

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