redis-command
Executes a Redis command via redis-cli and returns the response.
This record as markdown: /tools/io-github-dave-london-cargo/redis-command.md
What redis-command does on Cargo
AI agents invoke redis-command to trigger actions in Cargo. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why redis-command is rated High
This tool executes arbitrary Redis commands, which can range from benign reads to destructive operations (FLUSHALL, DEL, CONFIG REWRITE, etc.). Since the command is user-supplied and executed directly via redis-cli, it spans Read through Destructive depending on input.
From the tool's definition "Executes a Redis command via redis-cli" — runs arbitrary Redis commands against a live Redis instance
Attacks that exploit this kind of access
The rule that runs redis-command safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Cargo, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For redis-command, this is the rule to start with:
redis-command stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Cargo, apply this rule, and every redis-command call is checked against it from then on.
Questions about redis-command
Executes a Redis command via redis-cli and returns the response. It is categorised as a Execute tool in the Cargo MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Cargo MCP server in PolicyLayer and add a rule for redis-command: 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 Cargo. Nothing to install.
redis-command is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the redis-command 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 redis-command. 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.
redis-command is provided by the Cargo MCP server (Dave-London/Pare). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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