UnifAPI's episode on AI Agent vs Skill vs MCP vs API argues the four are separate layers in a public-data workflow, each owning a different job. It defines an API as the contract returning structured public records, MCP as the assistant-friendly connection path for Claude, ChatGPT, Codex, or other clients, a Skill as a repeatable task playbook, and an Agent as the user-facing role and decision loop. Using an Instagram creator example, a request moves down through agent, skill, MCP and API to gather live public evidence and returns as a cited answer. It stresses UnifAPI's scope is read-only: no posting, DMs, or private accounts, and directs users to Agents for an outcome, Skills for a workflow, MCP to connect an assistant, or the API catalog for custom integrations.
AI Agent, Skill, MCP, and API are not interchangeable. This visual guide shows what each layer owns—and how they work together in a live public-data workflow. Start with UnifAPI Agents: https://unifapi.com/agents Browse task-specific Skills: https://unifapi.com/skills Connect Claude, ChatGPT, or Codex with MCP: https://unifapi.com/mcp Explore the public-data API catalog: https://unifapi.com/apis In this episode: - API: the contract that returns structured public records - MCP: the assistant-friendly connection path - Skill: the repeatable task playbook - Agent: the role and decision loop you run inside your assistant UnifAPI supplies read-only marketing research Agents for SEO, AI visibility, influencer research, social listening, competitive intelligence, and more. They run inside the assistant you already use and work over one MCP connection. UnifAPI only reads public data in its current scope. It does not post, send DMs, or access private upstream social accounts.