Executes a Redis command via redis-cli and returns the response.
AI agents invoke redis-command to trigger actions in Lint. 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 runs arbitrary Redis commands through redis-cli. Redis commands can read data, but they can also write, delete, or flush entire databases (e.g., FLUSHALL, DEL, SET). Since the tool executes arbitrary commands whose effects depend on arguments, Execute is the appropriate category. The blast radius is high because a misused command could destroy or exfiltrate Redis data.
From the tool's definition 'Executes a Redis command via redis-cli and returns the response'
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 Lint, 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 Lint MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Lint 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 Lint. 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 Lint MCP server (Dave-London/Pare). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Lint, 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 Lint tools catalogued and risk-classified — across an index of 43,000+ MCP servers.