AI agents invoke query to trigger actions in SLayer. 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.
Given the server's purpose — converting intent into SQL and executing it against databases — a 'query' tool almost certainly runs compiled SQL against a database. This falls under Execute (running queries with external effects). The empty description lowers confidence, but the server context strongly implies query execution.
From the tool's definition Tool name is 'query' on a server described as compiling 'structured queries into correct, dialect-aware SQL' and supporting 'multi-stage queries'. Description is empty/uninformative.
Documented attack patterns abuse exactly the kind of access query gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and SLayer, and nothing reaches the server without passing your rules. This is the rule we recommend for query:
{
"version": "1",
"default": "deny",
"tools": {
"query": {
"limits": [
{
"counter": "query_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}query 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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query. It is categorised as a Execute tool in the SLayer MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the SLayer MCP server in PolicyLayer and add a rule for query: 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 SLayer. Nothing to install.
query 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 query 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 query. 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.
query is provided by the SLayer MCP server (motleyai/slayer). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from SLayer, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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20 SLayer tools catalogued and risk-classified — across an index of 43,000+ MCP servers.