calls_hangup
Hang up an active voice call by call_id. Use after calls.make when the agent decides to terminate before the callee does, or to abort a stuck call. Idempotent: returns success if the call is already terminal.
This record as markdown: /tools/io-github-saloprj-dialogbrain/calls-hangup.md
What calls_hangup does on Dialogbrain
AI agents invoke calls_hangup to trigger actions in Dialogbrain. 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.
| Parameter | Type | Required | Description |
|---|---|---|---|
reason | string | — | Short internal reason for ending the call (e.g. 'campaign timeout'). Stored on voice_sessions.metadata. |
call_id | string | Yes | Call ID returned by calls.make in _meta.call_id. |
Parameters from the server's own tool schema.
Why calls_hangup is rated High
This tool terminates an active voice call, which is an external real-world operation with immediate effect. While it is idempotent and not strictly destructive in a data sense, it executes an action on an external telephony system (ending a live call) that cannot be undone once the call is terminated.
From the tool's definition "Hang up an active voice call" and "terminate before the callee does, or to abort a stuck call"
Attacks that exploit this kind of access
The rule that runs calls_hangup safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Dialogbrain, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For calls_hangup, this is the rule to start with:
calls_hangup 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.
The button opens the PolicyLayer dashboard: create your workspace, connect Dialogbrain, apply this rule, and every calls_hangup call is checked against it from then on.
Questions about calls_hangup
Hang up an active voice call by call_id. Use after calls.make when the agent decides to terminate before the callee does, or to abort a stuck call. Idempotent: returns success if the call is already terminal. It is categorised as a Execute tool in the Dialogbrain MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
calls_hangup accepts 2 parameters: reason, call_id. Required: call_id. The full parameter table on this page comes from the server's own tool schema.
Register the Dialogbrain MCP server in PolicyLayer and add a rule for calls_hangup: 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 Dialogbrain. Nothing to install.
calls_hangup 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 calls_hangup 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 calls_hangup. 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.
calls_hangup is provided by the Dialogbrain MCP server (https://api.dialogbrain.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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