cache_append
Append a string to an existing value. Args: key: The key to append to value: String to append Returns: Success message or error message
This record as markdown: /tools/aws/cache-append.md
What cache_append does on AWS
AI agents use cache_append to create or update resources in AWS, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your AWS environment.
Why cache_append is rated Medium
This tool modifies existing cache data by appending a string to it. It is a reversible write operation (the original value can be restored), but misuse could corrupt cached data. No deletion, execution, or financial implications are present.
From the tool's definition Append a string to an existing value
Attacks that exploit this kind of access
The rule that runs cache_append safely
PolicyLayer is an MCP gateway: it sits between your AI agents and AWS, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For cache_append, this is the rule to start with:
cache_append stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect AWS, apply this rule, and every cache_append call is checked against it from then on.
Questions about cache_append
Append a string to an existing value. Args: key: The key to append to value: String to append Returns: Success message or error message. It is categorised as a Write tool in the AWS MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the AWS MCP server in PolicyLayer and add a rule for cache_append: 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 AWS. Nothing to install.
cache_append is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the cache_append 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 cache_append. 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.
cache_append is provided by the AWS MCP server (@awslabs/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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