proactive_context
Get contextually relevant tool and workflow suggestions based on time of day, day of week, and your usage patterns.
This record as markdown: /tools/heznpc-airmcp/proactive-context.md
What proactive_context does on AirMCP
AI agents call proactive_context to retrieve information from AirMCP without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why proactive_context is rated Low
This tool queries usage patterns and system state to return suggestions, similar to a search or recommendation engine. It has no side effects: it does not create, modify, execute, delete, or move resources. Even though it accesses personal usage data, the operation itself is non-destructive read access.
From the tool's definition Tool description states it 'Get[s] contextually relevant tool and workflow suggestions' — a retrieval operation with no modification or execution of external actions.
Attacks that exploit this kind of access
The rule that runs proactive_context safely
PolicyLayer is an MCP gateway: it sits between your AI agents and AirMCP, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For proactive_context, this is the rule to start with:
proactive_context is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect AirMCP, apply this rule, and every proactive_context call is checked against it from then on.
Questions about proactive_context
Get contextually relevant tool and workflow suggestions based on time of day, day of week, and your usage patterns. It is categorised as a Read tool in the AirMCP MCP Server, which means it retrieves data without modifying state.
Register the Air MCP server in PolicyLayer and add a rule for proactive_context: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches AirMCP. Nothing to install.
proactive_context is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the proactive_context rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for proactive_context. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
proactive_context is provided by the Air MCP server (airmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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