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
We curl-tested eight Twitter viewers the way an AI agent would. Most block scripts or hide data in JavaScript. Viewers suit people; agents need MCP or an API.
X post and profile JSON from the paid UnifAPI X API and MCP, field by field in X API v2 names: posts, media, profiles, pages, billing, errors.
Compare Peec AI, Profound, Botify, and UnifAPI for brand monitoring, enterprise reporting, website optimization, and pay-as-you-go data workflows.
UnifAPI is now built into OOMOL's open-source OpenConnector: connect once with a workspace key, share it with your team, and pair reads with OAuth writes.
How to use an AI Overview checker to inspect whether a query triggers an AI answer, which sources are cited, and what page gap to fix next.
How to use Instagram former usernames, public profile data, and active stories to verify account history before creator outreach or competitor research.
A practical workflow for checking keyword search volume, difficulty, CPC, and intent before turning a keyword list into a content brief.
How to use a Twitter profile viewer for creator vetting, competitor research, and account benchmarks without logging into the target account.
Key Google AI Overviews statistics: how often they trigger, their impact on clicks, who gets cited and what improves citation odds. All sourced.
AI agent context in 2026: rules vs skills, MCP servers, commands, subagents and hooks — and the simpler setup most operators actually need.
Why UnifAPI puts marketing Agents first, loads Skills as workflows, and keeps SEO, GEO, browser and social APIs as the evidence layer.
How UnifAPI packages Agents and Skills so operators can load workflows and connect the read-only public-data MCP server without building a custom app.
