Developer releases local events API covering SF Bay Area

By Splitfeed EditorialLast updated Oct 17, 2026, 19:20 UTC

On October 16, 2026, a developer posted to Hacker News announcing a self-built API and MCP server designed to aggregate local event data, specifically pop-ups, one-off gatherings, and concerts, currently scoped to the SF Bay Area. The project, framed as a "Things to Do" API, includes support for MCP server tool calls, meaning AI agents can query it directly rather than relying on live web searches or on-demand scraping to find event information.

The developer's stated motivation was a gap in the existing data landscape: no single provider aggregated the mix of informal and scheduled local events needed to power personalization and recommendation applications. The tool positions itself as a speed improvement over two common alternatives, having agents search the web in real time, or scraping pages on demand, both of which introduce latency that can degrade user-facing products. Whether the coverage depth and data freshness hold up against those alternatives in practice is the live question the project has not yet answered publicly.

None of the three camps have posted reactions to this release. The Pro-AI camp would typically welcome a purpose-built data layer like this as exactly the kind of infrastructure that makes AI-powered local discovery more reliable and less resource-intensive. The Anti-AI camp would likely raise questions about how the underlying event data is sourced, whether scraping or aggregation raises intellectual property or consent concerns, and what happens to smaller event organizers whose information gets routed through a commercial API without their involvement. The Middle Ground camp would probably acknowledge the practical utility while calling for transparency around data sourcing, update frequency, and the terms under which the API is offered.

The arguments that matter most here will likely surface as the project scales beyond the SF Bay Area or seeks commercial adoption. How the developer handles data provenance, attribution, and access pricing will determine whether the tool earns broader trust from developers and the communities whose events it indexes.