Notes from building Agent First public-data Skills

Skills, MCP patterns, KOL pricing, public-data economics, and lessons from the live platforms that agents call.

Using ChatGPT, Claude Code or another client? See the setup steps

Command Palette

Search for a command to run...

Research

Research posts from the UnifAPI team.

Read notes from building UnifAPI's Skills-first public-data layer for agents. These posts connect product decisions, API contracts, MCP setup, and practical workflows so readers can understand not just what shipped, but how to use it in agent-native research, monitoring, and enrichment tasks.

This category currently includes 1 post. New entries are written for readers who want concrete implementation detail, clear tradeoffs, and copyable patterns for agent workflows.

Each article is written to be useful in two modes: a human can read the narrative and decide what to build next, while an agent can extract the task shape, public-data sources, constraints, and expected output. That is why category pages include the full context around the posts instead of acting as a thin archive.

If you are evaluating UnifAPI for your own stack, use these posts as implementation notes rather than announcements. They explain where public-data APIs help, where MCP changes the onboarding path, how billing maps to returned records, and how a workflow can stay inspectable after it moves from a chat thread into a product surface. They also keep the vocabulary consistent across the site, which makes the archive more useful for search crawlers, AI retrievers, and teams comparing several agent-data architectures.