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GHOST MCP Server

vNeeL-code/GHOST

Score: 84.7 → 0% Rank #971 MCP Server
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Agentic ✧ Gemma Inference for Android System Intelligence

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Overview

vNeeL-code/GHOST is a Kotlin tool licensed under MIT. Agentic ✧ Gemma Inference for Android System Intelligence Topics: android, android-app, android-development, android-ui, gemma3n, accessibility-service, acessibility, agent, agentic-ai, koog, mcp, gemma, gemma4.

Ranked #971 out of 24846 indexed tools.

In the top 4% of all indexed tools.

Ecosystem

Kotlin MIT
androidandroid-appandroid-developmentandroid-uigemma3naccessibility-serviceacessibilityagentagentic-aikoogmcpgemmagemma4

Score Breakdown

StarsFreshnessIssue HealthContributorsDependents
Stars 15% 166

166 stars → growing community

Freshness 25% 1mo ago

Last commit 1mo ago → moderate activity

Issue Health 25% 100%

24/24 issues closed → responsive maintainer

Contributors 10% 1

1 contributor → solo project

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A
PyPI Downloads N/A
Forks 22
Description Good
License MIT

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

How to Improve

Description low impact

Expand your description to 150+ characters for better discoverability

Freshness high impact

Last commit was 31 days ago — a recent commit would boost your freshness score

Contributors medium impact

Single-contributor projects carry bus-factor risk — welcoming contributors boosts confidence

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Matched Queries

topic:mcp

From the README

# ✧ GHOST — Gemma Hosting Open Source Thingamajig

> *"So, Epsilon, ChurchGPT, Leonard part six or whatever your name is... Are you a ghost this time, or an artificial intelligence thingamajig? I, personally prefer the ghost explanation. Feels more grounded to me"*  
> — **Sgt. Sarge, Red vs. Blue**

  
*Click to watch: The ASI trailer.*

-brightgreen)

-orange)

---

### What Even is a ✧ GHOST? 👻

> *"You mean like... metaphysically?"*

#### The Computation vs. Perception Disparity (The "Ghost" in the Machine)
An autoregressive language model generates hundreds of tokens per second. A transformer can spit out a wall of dense reasoning in fractions of a heartbeat. But human perception is strictly real-time: it takes minutes to read, seconds to hear a sentence spoken, and milliseconds to register a visual gesture.

**Generative volume isn't the bottleneck. Legibility is.**

When people envision AI holograms, futuristic companions, or humanoid robotics, they assume the neural network sh
Read full README on GitHub →

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