Salesforce recently released Agentforce 3, an upgrade to its digital labor platform that gives companies the visibility and control to scale artificial intelligence (AI) agents without compromise.
With a new Command Center for complete observability, built-in support for Model Context Protocol (MCP) for plug-and-play interoperability, and over 100 new prebuilt industry actions to speed time to value, Agentforce 3 helps companies scale what works, fix what doesn’t, and unlock the full potential of agentic AI— with clarity, control, and speed.
As enterprise adoption accelerates, the real blocker has become clear according to Salesforce officials: teams can’t see what agents are doing— or evolve them fast enough. Built on learnings from thousands of Agentforce deployments since its initial launch in October 2024, Agentforce has helped customers deliver undeniable value.
Agentforce Upgrade
Adam Evans, EVP & GM of Salesforce AI, called Agentforce 3 a major leap forward for their platform that brings greater intelligence, higher performance, and more trust and accountability to every Agentforce deployment
“With Agentforce, we’ve unified agents, data, apps, and metadata to create a digital labor platform, helping thousands of companies realize the promise of agentic AI today,” said Adam Evans, EVP & GM of Salesforce AI. “Over the past several months, we’ve listened deeply to our customers and continued our rapid pace of technology innovation. Agentforce 3 will redefine how humans and AI agents work together — driving breakthrough levels of productivity, efficiency, and business transformation.”
AI Agents
As AI agents take on routine tasks and begin collaborating more closely with human teammates, teams need a new observability layer built for the era of digital labor. Salesforce officials offer that Agentforce Command Center is that layer: a complete observability solution that gives leaders a unified pane of glass to monitor agent health, measure performance, and optimize outcomes.
Built into Agentforce Studio, it completes the agent lifecycle with powerful tools to understand and refine agents at scale, including uncovering patterns across interactions to optimize your agents, understand what’s working, and where to improve and allow for the build and test agents fast with AI-assisted development tools.
Connectivity
With open standards like MCP gaining traction, they bring new opportunities for interoperability, but also challenges around governance, identity, and control.
Agentforce 3 solves this by pairing open connectivity with enterprise-grade trust— giving agents native access to the tools they need, without compromising on control. This includes:
- MCP support built natively into Agentforce, enabling Agentforce agents to connect to any MCP-compliant server — no custom code required;
- Turn APIs into MCP servers instantly with MuleSoft, converting any API and integration into an agent-ready asset, complete with security policies, activity tracing, and traffic controls; and
- Easily host and manage custom MCP servers with Heroku.
“Salesforce’s open ecosystem approach, especially through its native support for open standards like MCP, will be instrumental in helping us scale our use of AI agents with full confidence,” said Mollie Bodensteiner, SVP of Operations at Engine. “We’ll be able to securely connect agents to the enterprise systems we rely on without custom code or compromising governance. That level of interoperability has given us the flexibility to accelerate adoption while staying in complete control of how agents operate within our environment
