AI agents call get_context to retrieve information from Maestro without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The name suggests reading or retrieving context data rather than modifying, executing, or destructive operations. The vague description and '[Interno]' prefix suggest internal use. No evidence of side effects, code execution, deletion, or financial operations.
From the tool's definition Tool name 'get_context' indicates a retrieval operation; description '[Interno] Use' is uninformative and provides no detail on data scope or sensitivity.
Attacks that exploit this kind of access
[Interno] Use. It is categorised as a Read tool in the Maestro MCP Server, which means it retrieves data without modifying state.
Register the Maestro MCP server in PolicyLayer and add a rule for get_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 Maestro. Nothing to install.
get_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 get_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 get_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.
get_context is provided by the Maestro MCP server (matheus-gama-deluna/maestro). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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