This record as markdown: /tools/aiwerk-mcp-server-elevenlabs/dubbing-project-list.md
What dubbing_project_list does on Elevenlabs
AI agents call dubbing_project_list to retrieve information from Elevenlabs without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
cursor | string | null | — | Pass the `next_cursor` from a previous response to fetch the page after it. Omit for the first page. |
status | string | null | — | Filter to projects in this status: `queued`, `preparing`, `ready`, or `failed`. Omit to return every status. |
page_size | number | — | Number of projects per page. Clamped to between 1 and 100 rather than rejected, so a larger value returns a full page. |
sort_direction | string | — | Sort by creation time; newest first by default. |
Parameters from the server's own tool schema.
Why dubbing_project_list is rated Low
Even though dubbing_project_list only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Attacks that exploit this kind of access
The rule that runs dubbing_project_list safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Elevenlabs, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For dubbing_project_list, this is the rule to start with:
dubbing_project_list is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Elevenlabs, apply this rule, and every dubbing_project_list call is checked against it from then on.
Questions about dubbing_project_list
List Dubbing Projects. It is categorised as a Read tool in the Elevenlabs MCP Server, which means it retrieves data without modifying state.
dubbing_project_list accepts 4 parameters: cursor, status, page_size, sort_direction. The full parameter table on this page comes from the server's own tool schema.
Register the Elevenlabs MCP server in PolicyLayer and add a rule for dubbing_project_list: 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 Elevenlabs. Nothing to install.
dubbing_project_list is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the dubbing_project_list 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 dubbing_project_list. 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.
dubbing_project_list is provided by the Elevenlabs MCP server (@aiwerk/mcp-server-elevenlabs). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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