AI agents invoke vapi_end_call to trigger actions in Mcp Vapi. 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 triggers an external operation (terminating an active voice call) that has real-world side effects. While it doesn't delete data, it forcibly ends an ongoing call, which is an irreversible action on a live session.
From the tool's definition Force-end an active Vapi call. Useful if a call gets stuck or needs to be terminated from a workflow.
Attacks that exploit this kind of access
Force-end an active Vapi call. Useful if a call gets stuck or needs to be terminated from a workflow. It is categorised as a Execute tool in the Mcp Vapi MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Mcp Vapi MCP server in PolicyLayer and add a rule for vapi_end_call: 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 Mcp Vapi. Nothing to install.
vapi_end_call 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 vapi_end_call 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 vapi_end_call. 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.
vapi_end_call is provided by the Mcp Vapi MCP server (adhirajhangal/mcp-vapi). 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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