Seedance MCP

seedance_wait_task

Poll a Seedance task until completion or timeout. Returns task status, video URL, or error.

Instructions

Poll a Seedance task until completion or timeout.

Args: task_id: The task ID to poll. interval_seconds: Polling interval in seconds (default: SEEDANCE_POLL_INTERVAL). timeout_seconds: Maximum wait time in seconds (default: SEEDANCE_WAIT_TIMEOUT).

Returns: JSON with ok, task_id, status, video_url, error, and raw response.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "task_id": "<task_id>"
    },
    "name": "seedance_wait_task"
  }
}

Input Schema

Name	Required	Description	Default
`task_id`	Yes
`timeout_seconds`	No
`interval_seconds`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jun 25, 2026

TDQS

A4.4/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Given no annotations, the description carries the full burden of behavioral disclosure. It explains the polling behavior, the role of interval_seconds and timeout_seconds, and the return format (including ok, status, video_url, error). This provides sufficient transparency for an agent to understand tool behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: a one-line purpose statement, followed by a clear parameter list, and a return description. Every sentence adds value, and the information is front-loaded with the core action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity and the presence of an output schema, the description is fully complete. It covers all inputs, the polling behavior, and the expected return fields (including ok, error). No gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With schema description coverage at 0%, the description fully compensates by explaining each parameter: task_id (task to poll), interval_seconds (polling interval with default from environment), timeout_seconds (max wait). This adds meaning beyond the schema's property names and types.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Poll a Seedance task until completion or timeout.' It uses a specific verb ('poll') and resource ('Seedance task'), and distinguishes from siblings like 'seedance_get_task' (single status check without polling) and 'seedance_create_and_wait' (creates then waits).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly state when to use this tool versus alternatives. While the purpose implies usage for waiting on tasks, no direct guidance or exclusions are provided. The context of sibling tools suggests differentiation, but the description itself lacks usage instructions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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