WitnessAI introduced Agentic Control, a product the company says gives enterprises a single control plane to discover, monitor, and restrict AI agents, MCP servers, and tools across development environments and business workflows.
WitnessAI has launched Agentic Control, a governance product designed to help enterprises discover, monitor, and restrict AI agents, Model Context Protocol servers, and connected tools.
According to WitnessAI’s announcement published through PR Newswire, Agentic Control is intended to provide a single control plane for AI agents and related infrastructure used across integrated development environments, enterprise applications, agent frameworks, and custom workflows. The company says the product is aimed at organizations adopting agentic AI systems that can call tools, connect to external systems, and take actions beyond generating text.
In a company blog post titled “Introducing WitnessAI Agentic Control,” WitnessAI says the product can discover agents, MCP servers, tools, and downstream systems across an enterprise environment. The company describes the product as a way to create visibility into agent activity, including which tools are available to agents and which systems those tools can affect.
WitnessAI says Agentic Control includes a new MCP Catalog that scores tools and supports policy decisions. The company says organizations can use the product to enforce allow lists and block lists across agents, limiting which tools an agent may call and which MCP servers may be used.
On its AI governance product page, WitnessAI says its Control product can govern custom cloud agents and agentic IDEs, with enforcement at the tool-call and MCP-server level. The company also says the product can create audit records for blocked calls, which could help security and compliance teams review attempted agent actions.
The Model Context Protocol, often abbreviated as MCP, is used to connect AI systems to external tools and data sources. WitnessAI’s materials focus on MCP servers because they can expand what an AI agent is able to access or do. In enterprise settings, that can include connections to internal applications, code repositories, databases, ticketing systems, or other operational tools.
WitnessAI’s launch materials frame this as a governance challenge: as more teams connect AI agents to tools, companies need ways to understand what has been connected, which tools are risky, and whether agents are taking actions that violate policy. The company’s proposed answer is centralized discovery, scoring, and enforcement for agents, tools, and MCP servers.
The PR Newswire announcement says Agentic Control is designed to work across IDEs, applications, agent frameworks, and custom enterprise workflows. WitnessAI’s product page specifically mentions agentic IDEs and custom cloud agents, suggesting the company is targeting both software development environments and business-facing AI deployments.
That positioning reflects a broader enterprise concern: agentic systems often operate across multiple teams and platforms. A development team may use an AI coding assistant that can call tools inside an IDE, while another group may build a custom agent connected to internal software. WitnessAI says Agentic Control is intended to govern those agent interactions from one place rather than relying on separate controls for every environment.
The details available in the cited sources come from WitnessAI and its PR Newswire announcement. The company says Agentic Control can discover agent infrastructure, score tools through the MCP Catalog, enforce tool and MCP policies, and keep audit records for blocked calls. The sources do not include independent benchmark results or third-party evaluations of the product’s effectiveness.
For enterprises evaluating agentic AI systems, the launch points to a concrete area of AI security spending: controls around tool use and agent permissions. WitnessAI’s release suggests that governance for AI agents is moving beyond prompts and model access toward the operational layer where agents connect to tools, servers, and business systems.
WitnessAI has launched Agentic Control, a governance product designed to help enterprises discover, monitor, and restrict AI agents, Model Context Protocol servers, and connected tools.
The company says the product is aimed at organizations adopting agentic AI systems that can call tools, connect to external systems, and take actions beyond generating text.
The company describes the product as a way to create visibility into agent activity, including which tools are available to agents and which systems those tools can affect.
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