Structured local-data APIs for AI agents

What to build

A structured 'Things to Do' API/MCP server that aggregates local events, pop-ups, one-off happenings, and concerts into clean JSON endpoints, built specifically for AI agent tool-calling pipelines and consumer apps that need local activity data without scraping.

An indie developer's Show HN launch of a packaged local-events API signals a small but real gap: agent builders need structured, tool-callable local data feeds instead of slow scraping or heavyweight consumer APIs.

Demand

AI agent developers and consumer app builders building local discovery, concierge, or itinerary features want fast structured data they can plug into tool-calling pipelines, and existing options are either scraping-heavy or not designed for agent use.

• Hacker NewsShow hn

  Show HN: Things to Do API — 5 points, 2 comments. Poster describes an API/MCP for local events: pop-ups, one-off events, concerts, etc.

• Analyst synthesisOpportunity note

  Opportunity framing suggests indie AI app builders and agent developers need fast, structured, city- or niche-specific data feeds instead of slow live scraping for use cases like local events, deals, or inventory.

Stack

• FastAPI or Express for the API layer
• MCP SDK (Python or TypeScript) for agent tool-calling support
• Postgres or Supabase for storing normalized event records
• Scrapy or Playwright for source ingestion from venue/ticketing sites
• Eventbrite and Ticketmaster public feeds as seed data sources
• Stripe or a usage-based billing tool (e.g. Lago) for metered API keys

Solo + AI difficulty

The API/MCP wrapper itself is a weekend build with AI coding assistance; the hard, ongoing part is sourcing and normalizing fresh local event data across cities without breaking scrapers or hitting rate limits. Realistic time-to-MVP for one city or niche is 1-2 weeks, but reaching broad city coverage and keeping data fresh is the real multi-month grind.

Entry threshold

A single developer can scrape and structure one data vertical and expose it via a simple API plus MCP endpoint within a week or two, but scaling city or vertical coverage and keeping data fresh requires ongoing scraping/maintenance work that grows with each new market added.

Window

3-6 months

Where to find first users

• Show HN and Product Hunt launch
• r/SideProject and Indie Hackers for builder visibility
• MCP server directories and awesome-mcp-servers lists on GitHub
• Direct outreach to AI agent/app builder Discord and Slack communities (e.g. LangChain, AutoGPT-adjacent groups)

Competitors

• PredictHQ
• Eventbrite API
• Ticketmaster Discovery API

Counter-signals & risks

• No historical match or prior signal validates sustained demand for this niche API category, and the confirmation strength is weak.

• Structured local data APIs face incumbent competition from Google Places, Yelp, Eventbrite, and Ticketmaster, which may already serve agent integration needs.

• A single Show HN post with only 5 points and 2 comments is a weak signal of market demand and may not translate into paying customers or sustained usage.