Executes a Redis command via redis-cli and returns the response.
AI agents invoke redis-command to trigger actions in Http. 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.
This tool executes arbitrary Redis commands, which can span reading, writing, deleting data, or even administrative operations (FLUSHALL, DEL, CONFIG SET, etc.). Since it allows arbitrary command execution against a Redis instance, the most severe applicable category is Execute. Misuse could lead to data destruction or exfiltration, warranting high severity.
From the tool's definition 'Executes a Redis command via redis-cli' — runs arbitrary Redis commands through the CLI
Documented attack patterns abuse exactly the kind of access redis-command gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Http, and nothing reaches the server without passing your rules. This is the rule we recommend for redis-command:
{
"version": "1",
"default": "deny",
"tools": {
"redis-command": {
"limits": [
{
"counter": "redis-command_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}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.
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Executes a Redis command via redis-cli and returns the response. It is categorised as a Execute tool in the Http MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Http 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 Http. 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 Http MCP server (@paretools/http). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Http, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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202 Http tools catalogued and risk-classified — across an index of 43,000+ MCP servers.