AI agents invoke call_api to trigger actions in AWS Labs amazon-qindex MCP Server. 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.
The name 'call_api' suggests this tool makes external API calls, which falls under Execute due to triggering external operations. However, the description is entirely empty, making it impossible to determine the exact nature or scope of the API call. Severity is rated high given the broad potential blast radius of an arbitrary API call tool on an AWS/Amazon Q Business server.
From the tool's definition Tool name is 'call_api'; description is empty or uninformative.
Documented attack patterns abuse exactly the kind of access call_api gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and AWS Labs amazon-qindex MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for call_api:
{
"version": "1",
"default": "deny",
"tools": {
"call_api": {
"limits": [
{
"counter": "call_api_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} call_api 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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call_api. It is categorised as a Execute tool in the AWS Labs amazon-qindex MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the AWS Labs amazon-qindex MCP Server MCP server in PolicyLayer and add a rule for call_api: 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 Labs amazon-qindex MCP Server. Nothing to install.
call_api 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 call_api 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 call_api. 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.
call_api is provided by the AWS Labs amazon-qindex MCP Server MCP server (awslabs.amazon-qindex-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from AWS Labs amazon-qindex MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
805 AWS Labs amazon-qindex MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.