Gemini Fullstack LangGraph Quickstart vs hermes-agent
Side-by-side comparison of two AI agent tools
Short answer
- Gemini Fullstack LangGraph Quickstart has had no commit in 15 months; hermes-agent is actively maintained (33,428 commits in the last 90 days).
- hermes-agent is growing faster: +5,710 GitHub stars in the last 30 days vs +48 for Gemini Fullstack LangGraph Quickstart.
- Pick Gemini Fullstack LangGraph Quickstart for: get started with building Fullstack Agents using Gemini 2.5 and LangGraph. Pick hermes-agent for: the agent that grows with you.
From GitHub data refreshed daily.
Gemini Fullstack LangGraph Quickstartopen-source
Get started with building Fullstack Agents using Gemini 2.5 and LangGraph
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hermes-agentopen-source
The agent that grows with you
Metrics
| Gemini Fullstack LangGraph Quickstart | hermes-agent | |
|---|---|---|
| Stars | 18.3k | 250.9k |
| Star velocity /mo | 48.473684210526315 | 5.7k |
| Commits (90d) | 0 | 33.4k |
| Releases (6m) | 0 | 10 |
| Overall score | 0.23129714016880468 | 0.946551175635728 |
Pros
- +Complete fullstack implementation with React frontend and LangGraph backend, providing a full working example of research-augmented conversational AI
- +Demonstrates advanced agent capabilities including iterative search refinement, knowledge gap identification, and citation generation for reliable responses
- +Built-in development experience with hot-reloading for both frontend and backend, plus LangGraph UI for debugging agent workflows
Cons
- -Requires Google Gemini API key and Google Search API access, creating external dependencies and potential ongoing costs
- -Limited to Google's search infrastructure, which may not cover all research needs or data sources
- -Appears to be a demonstration/learning project rather than a production-ready framework for enterprise applications
Use Cases
- •Learning how to build research-augmented conversational AI systems with modern tools like LangGraph and Gemini models
- •Prototyping AI agents that need dynamic web search capabilities for customer support, research assistance, or knowledge base applications
- •Building educational or research tools that require real-time information gathering with proper source attribution and citations
FAQ
- Which is more popular, Gemini Fullstack LangGraph Quickstart or hermes-agent?
- hermes-agent has more GitHub stars (250,877 vs 18,347).
- Which is more actively developed, Gemini Fullstack LangGraph Quickstart or hermes-agent?
- hermes-agent had more commits in the last 90 days (33,428 vs 0).
- Should I use Gemini Fullstack LangGraph Quickstart or hermes-agent?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.