In November 2024, Anthropic made waves with the launch of the open-source Model Context Protocol (MCP). The excitement was well-founded: MCP promised to bring order to the chaotic landscape of connecting large language models (LLMs) with external systems.
What began as a single provider's initiative evolved at breathtaking speed, quickly becoming the de facto standard for AI connectivity. Within months, industry titans like OpenAI and Google officially threw their weight behind the protocol, signaling an unusually early consensus among major players.
This momentum culminated in late 2025, when the protocol was transferred to the Agentic AI Foundation (AAIF), part of the Linux Foundation. This transfer cemented MCP as a truly vendor-agnostic standard for the enterprise.
The MCP ecosystem is expanding at an unprecedented pace. We are seeing a surge in official MCP servers from major software vendors, complemented by a vibrant open-source community that rapidly fills any gaps.
This broad adoption has quickly made MCP servers a foundational component of modern AI infrastructure. The reason is simple: They bridge the critical gap between an AI's static training data and the dynamic, real-time reality of the enterprise.
Beyond just data access, MCP empowers models to act. By giving AI the “arms and legs” to execute tasks, MCP transforms passive chatbots into capable agents that deliver genuine operational value.
Automic Automation is widely recognized as a market leader and is trusted to orchestrate the most business-critical processes of the world’s largest enterprises. Today, Automic leverages MCP directly within the platform.
The solution features an integrated “intelligent assistant” that goes beyond a simple help bot; it empowers users to interact with technical documentation, query real-time system data, and even direct user interface elements using natural language.
Intelligent list filtering is one its standout capabilities: Instead of manually constructing complex filter logic, users can simply describe the data they need. This transforms a traditionally tedious administrative task into a seamless, conversational command.
The revolution extends far beyond the intelligent assistant. Thanks to specialized new building blocks, Automic enables teams to make AI a core structural component of modern process automation. LLMs can now interpret natural language inputs to autonomously parameterize workflows or determine the correct execution branch.
This capability reaches its full potential when paired with MCP. Automic serves as the central command center for this ecosystem, allowing administrators to configure and authorize external MCP servers explicitly.
To see this in action, consider a real-world enterprise workflow: An organization centrally manages MCP server connections to a ticketing tool like Broadcom’s Rally and a knowledge repository like VMware's Private AI service. An AI-powered job within an Automic workflow can securely leverage these authorized MCP connections to read recently opened Rally tickets, retrieve relevant product documentation from the Private AI knowledgebase, and automatically enrich the ticket with its analysis.
From there, subsequent steps in the Automic workflow seamlessly handle the classification and appropriate enterprise routing of the ticket. This centralization is a game changer for the enterprise: It transforms AI from a “black box” into a governed infrastructure, ensuring that models have access only to approved tools and data to execute these complex, multi-system processes safely.
In a truly agent-based ecosystem, value flows in two directions: consuming intelligence and executing actions. Automic is designed to do both.
While it acts as an MCP client to leverage external data, it significantly amplifies its value by providing its own native MCP server. This critical feature exposes Automic’s robust orchestration capabilities to the outside world, allowing third-party AI agents to safely access and control enterprise workflows. In essence, it turns Automic into a library of “skills” that any authorized agent in your network can use.
This strategic pivot toward an open, agent-based architecture has been emphatically validated throughout the industry. In the 2025 EMA Radar for Workload Automation, Broadcom was named a Value Leader, earning specific distinction for "Excellence in Agentic Automation Enablement."
The report highlighted Automic’s early and robust adoption of MCP as a defining differentiator, positioning the platform not just as a tool for today, but as the essential execution layer for tomorrow's AI-driven enterprise. As organizations transition from simple chatbots to complex, autonomous multi-agent workforces, this recognition confirms a critical truth: To build AI that works safely and effectively, you need Automic.
To learn more, be sure to see our webcast, “Automic Automation V26: Establishing the Intelligent Control Plane for Enterprise AI."