threads_delete
🗑️ PERMANENTLY delete conversation thread(s) and their messages + user-facing state (tags, assignments, drafts, reminders, RAG chunks). Destructive and NOT undoable — requires confirm=true. Pass thread_id for one, or thread_ids for a bulk delete. Kept intentionally: call history (voice_sessions)...
This record as markdown: /tools/io-github-saloprj-dialogbrain/threads-delete.md
What threads_delete does on Dialogbrain
AI agents call threads_delete to permanently remove resources in Dialogbrain, typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
| Parameter | Type | Required | Description |
|---|---|---|---|
confirm | boolean | Yes | Must be true to actually delete — a safety gate for this destructive action. |
thread_id | integer | — | A single thread ID to delete. Use this OR thread_ids. |
thread_ids | array | — | Multiple thread IDs to delete in one call (bulk). Use this OR thread_id. |
Parameters from the server's own tool schema.
Why threads_delete is rated Critical
This tool irreversibly deletes data (conversation threads, messages, associated metadata) with no recovery mechanism. While some system records (call history, usage/billing, traces) are preserved, the primary user-facing conversation data and state are permanently removed and cannot be restored. The 'Destructive' category is the highest applicable severity for tools that cannot be undone.
From the tool's definition 'PERMANENTLY delete conversation thread(s) and their messages + user-facing state (tags, assignments, drafts, reminders, RAG chunks).
Attacks that exploit this kind of access
The rule that runs threads_delete 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 threads_delete, this is the rule to start with:
threads_delete is removed from the agent's tool list entirely, so the agent never calls it. The rest of the server keeps working.
The button opens the PolicyLayer dashboard: create your workspace, connect Dialogbrain, apply this rule, and every threads_delete call is checked against it from then on.
Questions about threads_delete
🗑️ PERMANENTLY delete conversation thread(s) and their messages + user-facing state (tags, assignments, drafts, reminders, RAG chunks). Destructive and NOT undoable — requires confirm=true. Pass thread_id for one, or thread_ids for a bulk delete. Kept intentionally: call history (voice_sessions), usage/billing, traces, and outreach dedup are NOT removed. Note: for a live synced channel (Telegram/WhatsApp) this clears the LOCAL copy; a new inbound can re-create the thread on next sync. For livechat/voice/test/duel threads it's effectively permanent. It is categorised as a Destructive tool in the Dialogbrain MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
threads_delete accepts 3 parameters: confirm, thread_id, thread_ids. Required: confirm. 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 threads_delete: 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.
threads_delete is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the threads_delete 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 threads_delete. 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.
threads_delete 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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