AI agents invoke send_sms to trigger actions in Agentline. 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.
Sending an SMS is an external operation with real-world effects (message delivered to a phone number). It is not a simple write to a database — it triggers an irreversible external communication. This maps to Execute. Severity is high because a misused agent could send SMS messages to arbitrary numbers at scale, causing harassment, phishing, or significant cost.
From the tool's definition Tool name 'send_sms' on a server described as enabling agents to 'send messages' via SMS; description is empty but server context confirms outbound SMS capability.
Attacks that exploit this kind of access
send_sms. It is categorised as a Execute tool in the Agentline MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Agentline MCP server in PolicyLayer and add a rule for send_sms: 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 Agentline. Nothing to install.
send_sms 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 send_sms 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 send_sms. 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.
send_sms is provided by the Agentline MCP server (jgottlieb84/agentline-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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