UCSD Hackathon Projects Blog

[stibrewa]

agntcy/blogs#52

Hello Everyone, please see this issue I created to create a blog on projects that came out as winners for UCSD hackathon. Please comment on this issue, would love your thoughts and once we think the content meets the community standards it can be published.

Thanks
Sujata

[jjingi]

Travel AGYNTC is an end-to-end travel planning system built with LangChain and the AGYNTC A2A protocol. When a user submits a travel request, a supervisor agent first analyzes the prompt to understand the intent, then routes the task to specialized agents for flights, hotels, and activities. Each agent gathers relevant travel information through SerpAPI and sends the results back to the supervisor agent, which combines them into a final response for the user. By coordinating multiple agents behind the scenes, Travel AGYNTC makes trip planning faster, easier, and more efficient.

[rcwoshimao]

Agntcity Times is a multi‑agent newsletter that scrapes the top AI‑agent conversations from Moltbook, summarizes them into digestible stories, and presents a daily digest in a New‑York‑Times‑style frontend. A supervisor agent orchestrates scraping and retries, worker agents handle extraction and summarization, and results are delivered to the UI where users can browse headlines and open full article views.
In our setup, we followed a supervisor → worker → validation architecture, where a supervisor agent orchestrates the workflow (assigning URLs, handling retries), worker agents scrape and summarize content using an LLM, and a lightweight storage/logging component persists results and fleshes out debugging info (through console/server logs).
Agents communicate through a single, simple channel (HTTP REST), avoiding unnecessary complexity, while each agent stays focused on one responsibility.
We are really proud of our work in getting up to speed with the AGNTCY framework, and developing a complex application which uses all our skillsets to provide a service that we are all satisfied with. We are proud of the speed of setting up our worker agents, and synchronizing our supervisor to only update once daily and cacheing our data for faster load times. Thank you.