Agent Marketplace / Discovery

The agent marketplace concept mirrors the evolution of software distribution: just as enterprise software moved from custom builds to packaged applications and then to SaaS, agentic AI is moving from fully custom agent development toward a marketplace model where specialized agents are published, versioned, and consumed. A finance team can find a pre-built accounts payable reconciliation agent; an IT team can deploy a security alert triage agent; a marketing team can install a competitive intelligence agent — all without an internal AI engineering team building from scratch.

From the technical perspective, agent discovery requires standardized interfaces. Emerging standards like Anthropic's Model Context Protocol (MCP) and Google's Agent-to-Agent protocol are creating the interoperability layer that makes agent marketplaces practical: a published agent advertises its capabilities, input/output schemas, and required tool permissions in a machine-readable format, allowing orchestration platforms to compose agents dynamically.

For the enterprise, the marketplace model introduces new procurement and governance challenges alongside its productivity benefits. Procurement teams need to evaluate agent providers with the same rigor applied to SaaS vendors: data handling practices, SLA commitments, update policies, and compliance certifications. IT and security teams need a mechanism to review and approve agents before deployment, analogous to software procurement review — the "shadow agent" problem (employees deploying unapproved agents with access to company data) is a real and emerging governance risk.