arc-llm-lab

MCP server · GitHub · ★ 8 · graded 2026-10-23Source linked

Run LLMs on Intel Arc (B60, B580, B570, B50, B70, A770) with llama.cpp Vulkan: benchmarks, tuning, agent reliability evals, raw data.

No outside reports on file

arc-llm-lab is distributed via GitHub (edagher92-coder/arc-llm-lab); review its source code, dependencies, and requested permissions before use.

Based on public adoption and transparency signals as of Oct 23, 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 executionNo shell command runner notedLOW
Network reachLocal or standard API callsLOW
CredentialsNo API token requiredLOW
Package sourceGitHub (edagher92-coder/arc-llm-lab)PUBLIC

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

Install

No npm or PyPI package is listed. Install from source: github.com/edagher92-coder/arc-llm-lab ↗

All setup options ↓

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About Arc LLM Lab

Arc LLM Lab is an MCP server focused on Data & databases: Run LLMs on Intel Arc (B60, B580, B570, B50, B70, A770) with llama.cpp Vulkan: benchmarks, tuning, agent reliability evals, raw data.

It is hosted on GitHub at edagher92-coder/arc-llm-lab (8 GitHub stars). Based on its public metadata, it operates with standard local or API scope without broad shell execution flags noted.

Setup

These use the package this listing points to. Check the project’s own instructions before running anything.

No npm or PyPI package is listed for this MCP server. Source code and setup steps: github.com/edagher92-coder/arc-llm-lab.

Why this grade

DD — High risk signals

Signal-based grade (1/7 points): public source code. This reflects adoption and transparency, not a code review.

Popularity and upkeep

13/100

GitHub stars: 8
Listing last refreshed: 2026-10-23

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

Security reports

No reports found for this package in our research (last checked 2026-10-29).

Check a specific version →

Risks to watch for

Dependency & version pinning: Distributed via GitHub (edagher92-coder/arc-llm-lab). 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 Arc LLM Lab?

Arc LLM Lab does not publish a standalone npm or PyPI package. Clone or follow the setup instructions in its source repository at github.com/edagher92-coder/arc-llm-lab.

Are there security reports about Arc LLM Lab?

No reports found for this package in our research (last checked 2026-10-29). Arc LLM Lab currently holds Grade D (High risk signals) based on public adoption and transparency signals. Review the permissions and source repository before granting access to local files, shell commands, or API keys.

Is Arc LLM Lab actively maintained?

Arc LLM Lab has 8 GitHub stars. Our directory data was last refreshed on 2026-10-23. Check recent commit activity, release tags, and open issues at github.com/edagher92-coder/arc-llm-lab before pinning it in production.

What are alternatives to Arc LLM Lab?

Compare Arc LLM Lab side by side with similar MCP servers in the Related tools section on this page, or browse all MCP servers on AgentArmorHQ.

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

AgentArmorHQ Risk Grade D for Arc LLM Lab

GitHub README Markdown:

markdown

[![AgentArmorHQ Risk Grade for Arc LLM Lab](https://agentarmorhq.com/api/badge/edagher92-coder-arc-llm-lab)](https://agentarmorhq.com/skills/edagher92-coder-arc-llm-lab)

HTML embed:

html

<a href="https://agentarmorhq.com/skills/edagher92-coder-arc-llm-lab"><img src="https://agentarmorhq.com/api/badge/edagher92-coder-arc-llm-lab" alt="AgentArmorHQ Risk Grade for Arc LLM Lab" height="20" /></a>

Terminal check:

terminal

curl -fsSL https://agentarmorhq.com/api/cli | node --input-type=module - check "edagher92-coder-arc-llm-lab"

Share with your security lead

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

### AgentArmorHQ Security Review Memo: arc-llm-lab
- **Listing URL:** https://agentarmorhq.com/skills/edagher92-coder-arc-llm-lab
- **Type:** App connector
- **Risk Grade:** Grade D (High risk signals)
- **Outside Security Advisories on File:** 0
- **Public Adoption:** 8 GitHub stars

#### Permission & Blast-Radius Signals
- **Local files:** No local folder access noted
- **Command execution:** No shell command runner noted
- **Network reach:** Local or standard API calls
- **Credentials:** No API token required
- **Package source:** GitHub (edagher92-coder/arc-llm-lab)

#### Recommended Hardened Setup
- **Source Repo:** https://github.com/edagher92-coder/arc-llm-lab
- **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 23, 2026. Our opinion, not a code audit or security guarantee._

Key facts

Type: App connector
Publisher: edagher92-coder
Source code: github.com/edagher92-coder/arc-llm-lab
Est. context load: ~550 tokens / turn (~3 tool schemas, 0.27% of 200k context)
Popularity: 8 GitHub stars
Last updated: 2026-10-23
Last graded: 2026-10-23

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