AI agents call get_tokens to retrieve information from Sdds without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool performs a straightforward data retrieval operation on a list of design system tokens. This has no side effects, cannot modify state, and poses minimal risk if misused by an AI agent. It falls clearly into the Read category as a query/fetch operation.
From the tool's definition Tool description states it 'retrieves the list of...tokens' — a read-only retrieval operation with no modification, deletion, or execution capability.
Attacks that exploit this kind of access
This tool retrieves the list of ${libraryName} tokens that can be reused in custom components. It is categorised as a Read tool in the Sdds MCP Server, which means it retrieves data without modifying state.
Register the Sdds MCP server in PolicyLayer and add a rule for get_tokens: 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 Sdds. Nothing to install.
get_tokens 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_tokens 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_tokens. 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_tokens is provided by the Sdds MCP server (@salutejs/sdds-mcp). 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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