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poll_rodin_job_status

Check completion status of Hyper3D Rodin 3D model generation tasks in Blender, using subscription keys or request IDs to monitor progress until final determination.

Instructions

Check if the Hyper3D Rodin generation task is completed.

For Hyper3D Rodin mode MAIN_SITE:
    Parameters:
    - subscription_key: The subscription_key given in the generate model step.

    Returns a list of status. The task is done if all status are "Done".
    If "Failed" showed up, the generating process failed.
    This is a polling API, so only proceed if the status are finally determined ("Done" or "Canceled").

For Hyper3D Rodin mode FAL_AI:
    Parameters:
    - request_id: The request_id given in the generate model step.

    Returns the generation task status. The task is done if status is "COMPLETED".
    The task is in progress if status is "IN_PROGRESS".
    If status other than "COMPLETED", "IN_PROGRESS", "IN_QUEUE" showed up, the generating process might be failed.
    This is a polling API, so only proceed if the status are finally determined ("COMPLETED" or some failed state).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`subscription_key`	No
`request_id`	No

Implementation Reference

src/blender_mcp/server.py:803-845 (handler)

The main handler function for the 'poll_rodin_job_status' MCP tool. It forwards the polling request to the Blender addon via socket command, using either a subscription_key (MAIN_SITE mode) or request_id (FAL_AI mode). Includes input validation via parameters and comprehensive docstring describing usage for both modes. The @mcp.tool() decorator registers it with the FastMCP server.

@mcp.tool()
def poll_rodin_job_status(
    ctx: Context,
    subscription_key: str=None,
    request_id: str=None,
):
    """
    Check if the Hyper3D Rodin generation task is completed.

    For Hyper3D Rodin mode MAIN_SITE:
        Parameters:
        - subscription_key: The subscription_key given in the generate model step.

        Returns a list of status. The task is done if all status are "Done".
        If "Failed" showed up, the generating process failed.
        This is a polling API, so only proceed if the status are finally determined ("Done" or "Canceled").

    For Hyper3D Rodin mode FAL_AI:
        Parameters:
        - request_id: The request_id given in the generate model step.

        Returns the generation task status. The task is done if status is "COMPLETED".
        The task is in progress if status is "IN_PROGRESS".
        If status other than "COMPLETED", "IN_PROGRESS", "IN_QUEUE" showed up, the generating process might be failed.
        This is a polling API, so only proceed if the status are finally determined ("COMPLETED" or some failed state).
    """
    try:
        blender = get_blender_connection()
        kwargs = {}
        if subscription_key:
            kwargs = {
                "subscription_key": subscription_key,
            }
        elif request_id:
            kwargs = {
                "request_id": request_id,
            }
        result = blender.send_command("poll_rodin_job_status", kwargs)
        return result
    except Exception as e:
        logger.error(f"Error generating Hyper3D task: {str(e)}")
        return f"Error generating Hyper3D task: {str(e)}"

src/blender_mcp/server.py:804-808 (schema)
Function signature providing type hints and default values for tool parameters: subscription_key (str, optional for MAIN_SITE mode) and request_id (str, optional for FAL_AI mode). The docstring provides detailed input/output schema description.
```
def poll_rodin_job_status(
    ctx: Context,
    subscription_key: str=None,
    request_id: str=None,
):
```

src/blender_mcp/server.py:917-920 (helper)

Usage instruction in the asset_creation_strategy prompt, guiding when and how to use the poll_rodin_job_status tool as part of the Hyper3D generation workflow.

2. Poll the status
    - Use poll_rodin_job_status() to check if the generation task has completed or failed
3. Import the asset
    - Use import_generated_asset() to import the generated GLB model the asset

src/blender_mcp/server.py:803-803 (registration)
The @mcp.tool() decorator registers the poll_rodin_job_status function as an MCP tool with the FastMCP server instance.
```
@mcp.tool()
```

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv1.0.0Jan 3, 2026
- addedInput schema / title
```
Added value: +"poll_rodin_job_statusArguments"
```
First observedOct 22, 2025

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations, the description carries the full behavioral disclosure burden. It discloses mode-specific statuses, progress states, failure conditions, and terminal states: 'Done', 'Canceled', 'COMPLETED', 'IN_PROGRESS', and 'IN_QUEUE'. It does not describe exact response shape or polling timeout/block behavior, but the core decision logic is clear.

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

Conciseness4/5

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

The description is well organized into two mode sections with clear parameter and status explanations. It is still reasonably tight, though the 'polling API, so only proceed' caution is repeated in both sections, which slightly reduces conciseness.

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

Completeness4/5

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

Given the absence of annotations and output schema, the description covers the important status logic, failure conditions, and decision rule with enough clarity for an agent. It is slightly incomplete because it does not differentiate itself from the sibling get_hyper3d_status tool or describe the response structures in more detail.

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

Parameters4/5

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

The input schema contains two arbitrary string fields with no descriptions and 0% schema coverage. The description compensates by explaining that subscription_key belongs to MAIN_SITE mode and request_id belongs to FAL_AI mode, both obtained from the generate step. It still does not explicitly state that exactly one parameter is required depending on mode.

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 opens with a specific verb-resource pair: checking whether the Hyper3D Rodin generation task is completed. It clearly separates behavior across MAIN_SITE and FAL_AI modes, which makes the tool's role in the generation pipeline obvious and distinguishes it from sibling generation/import tools.

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

Usage Guidelines4/5

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

It gives useful usage context: it is a polling API, should be called when checking generation status, and should only proceed when terminal statuses are observed. However, it does not explicitly name alternatives such as get_hyper3d_status or describe when this tool is not appropriate.

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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