Controlling AI Agents with Notion MCP and Actra Governance
The article describes a system that combines the Notion MCP (Model Context Protocol) for AI agent capabilities and the Actra governance layer to enforce policies and control the agent's actions.
Why it matters
This approach to governing AI agents can enable safe, auditable, and policy-driven execution of real-world workflows.
Key Points
- 1Separates capability (MCP) from control (Actra) for AI agents
- 2Actra evaluates every tool call before execution to enforce policies
- 3Provides input validation, context-based control, and explicit reasoning for blocked actions
- 4Enables safe AI agents for real-world workflows with clear auditability
Details
The core idea is to use MCP as the capability layer, exposing Notion workspace actions that the AI agent can invoke. However, the Actra governance layer is introduced to evaluate each tool call before execution, enforcing policies such as blocking empty searches or writes in safe mode. This creates a system where the agent knows about the available tools but cannot execute them freely. Instead, Actra deterministically decides whether the agent's actions are allowed based on the defined policies. This approach transforms AI agents from 'systems that can act' to 'systems that can act safely, predictably, and under control'. The author demonstrates this with a Notion MCP-based agent, showcasing how Actra can prevent unauthorized actions, restrict unsafe API calls, and only allow whitelisted operations.
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