What is the way-back-home MCP server?

gca-americas/way-back-home — 🚀 Way Back Home AgentRank score: 53.6/100.

Is the way-back-home MCP server actively maintained?

The way-back-home MCP server was last committed 1mo ago and has 6 contributors. Issue health: 0% of issues resolved. AgentRank freshness score reflects real-time maintenance activity.

way-back-home MCP Server

Name: gca-americas/way-back-home
Rating: 3.1 (1 reviews)
Author: gca-americas

gca-americas/way-back-home

Score: 53.6 Rank #12193 Search & RAG

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Overview

gca-americas/way-back-home is a Python tool licensed under Apache-2.0. 🚀 Way Back Home Topics: a2a, adk, agents, bigquery, google-cloud, mcp, multimodal, rag.

Ranked #12193 out of 24846 indexed tools.

Ecosystem

Python Apache-2.0

a2aadkagentsbigquerygoogle-cloudmcpmultimodalrag

Score Breakdown

Stars 15% 99

99 stars → early stage

Freshness 25% 1mo ago

Last commit 1mo ago → moderate activity

Issue Health 25% 0%

0/49 issues closed → many open issues

Contributors 10% 6

6 contributors → small team

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A

PyPI Downloads N/A

Forks 58

Description Brief

License Apache-2.0

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

How to Improve

Description low impact

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Freshness high impact

Last commit was 40 days ago — a recent commit would boost your freshness score

Issue Health high impact

You have 49 open vs 0 closed issues — triaging stale issues improves health

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Markdown

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HTML

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HTML

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Details

Stars: 99
Forks: 58
Open Issues: 49
Closed Issues: 0
Contributors: 6
Dependents: —
Language: Python
License: Apache-2.0
Last Commit: 1mo ago

Matched Queries

topic:mcp

From the README

- # 🚀 Way Back Home

**An immersive AI workshop platform where participants learn to build intelligent agents while rescuing a stranded space explorer.**

Way Back Home is a hands-on workshop experience that teaches Google Cloud AI technologies through an engaging narrative. Participants crash-land on an alien planet and must use AI to identify themselves, analyze their surroundings, and coordinate rescue efforts.

## 🎮 The Experience

You're a space explorer whose ship has crashed on an uncharted planet. Your rescue beacon is offline, and you're scattered across the surface with other survivors. To get home, you must:

| Level | Mission | AI Skills Learned |
|-------|---------|-------------------|
| **Level 0** | Generate your explorer identity | Multi-turn image generation, Gemini (Nano Banana) |
| **Level 1** | Pinpoint your crash location | Multi-agent systems, MCP servers, ADK, parallel processing |
| **Level 2** | Process incoming SOS signals | Event-driven agents, A2A communic

Read full README on GitHub →