The following sections describe common usage patterns for Ontology MCP.
You can use Ontology MCP with desktop agents such as Claude.ai, Microsoft Copilot Studio, and Gemini Enterprise. In these use cases, Ontology MCP enriches the desktop agent with the ability to connect to your organization's source of truth, read and write data, and execute actions governed by your ontology.
This pattern enables human-agent symbiosis: both the human user and the AI agent operate on the same shared data, logic, actions, and governance. For example, a user working in Microsoft Teams can ask a Copilot Studio agent to create a task in the ontology, and the resulting data is immediately visible to other users and applications that share the same ontology.
Organizations that run agentic workflows using external frameworks such as Google Agent Development Kit (ADK), Microsoft Agent Framework, or OpenAI SDK can use Ontology MCP to access Foundry data and logic through a common interface. Agents in these frameworks interact with Ontology MCP the same way they interact with other systems, using MCP as a standard protocol.
Developers can combine multiple MCP servers to build richer agent capabilities. For example, an agent can use Perplexity MCP for web search alongside Ontology MCP for reading and writing ontology data, enabling workflows that span both external knowledge and your organization's source of truth.
Ontology MCP can serve as the memory and tracking layer for headless agent workflows. Headless agents operate without direct human supervision and can use Ontology MCP to both read and write from the organization's source of truth.
Because every action the agent performs through Ontology MCP is recorded in the ontology, this pattern provides auditability for unsupervised operations. You can use any agent framework, such as Anthropic SDK or Google ADK, to build headless workflows that run in response to ontology changes or on a scheduled basis.