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Meta Muse MCP Server by useapi.net (third-party)

by net.useapi
OverviewDiscussionsAdmin

Generate a video

muse_generate_video

Make one video with Muse from a prompt, optionally from input images (image_1..image_9), videos (video_1..video_3, e.g. to edit) and audio (audio_1..audio_3) as asset ids. Say the aspect ratio and any spoken lines in the prompt. Waits up to ~50 s; videos usually take longer, so expect a jobid to pick up with muse_get_job (wait: true). Uses the account's weekly Muse allowance. POST /jobs/video.

Input Schema

NameRequiredDescriptionDefault
emailNoThe Muse account to run on. When omitted, the account that holds the inputs, or a healthy account with allowance left.
promptYesWhat to make, up to 5000 characters. Name the inputs image_1, video_1, audio_1… and say the aspect ratio and the spoken lines.
audio_1NoInput audio 1: an asset id from muse_upload_asset, muse_list_assets, a job result or a chat file. Name it audio_1 in the prompt.
audio_2NoInput audio 2: an asset id from muse_upload_asset, muse_list_assets, a job result or a chat file. Name it audio_2 in the prompt.
audio_3NoInput audio 3: an asset id from muse_upload_asset, muse_list_assets, a job result or a chat file. Name it audio_3 in the prompt.
image_1NoInput image 1: an asset id from muse_upload_asset, muse_list_assets, a job result or a chat file. Name it image_1 in the prompt.
image_2NoInput image 2: an asset id from muse_upload_asset, muse_list_assets, a job result or a chat file. Name it image_2 in the prompt.
image_3NoInput image 3: an asset id from muse_upload_asset, muse_list_assets, a job result or a chat file. Name it image_3 in the prompt.
image_4NoInput image 4: an asset id from muse_upload_asset, muse_list_assets, a job result or a chat file. Name it image_4 in the prompt.
image_5NoInput image 5: an asset id from muse_upload_asset, muse_list_assets, a job result or a chat file. Name it image_5 in the prompt.
image_6NoInput image 6: an asset id from muse_upload_asset, muse_list_assets, a job result or a chat file. Name it image_6 in the prompt.
image_7NoInput image 7: an asset id from muse_upload_asset, muse_list_assets, a job result or a chat file. Name it image_7 in the prompt.
image_8NoInput image 8: an asset id from muse_upload_asset, muse_list_assets, a job result or a chat file. Name it image_8 in the prompt.
image_9NoInput image 9: an asset id from muse_upload_asset, muse_list_assets, a job result or a chat file. Name it image_9 in the prompt.
video_1NoInput video 1: an asset id from muse_upload_asset, muse_list_assets, a job result or a chat file. Name it video_1 in the prompt.
video_2NoInput video 2: an asset id from muse_upload_asset, muse_list_assets, a job result or a chat file. Name it video_2 in the prompt.
video_3NoInput video 3: an asset id from muse_upload_asset, muse_list_assets, a job result or a chat file. Name it video_3 in the prompt.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / properties / replyRef
      Removed value: -{
-  "description": "Optional reference echoed back in the job record.",
-  "maxLength": 1024,
-  "type": "string"
-}
  2. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only supply the generic non-read-only/open-world profile; the description adds the substantive traits: a ~50 s wait cap, that the call usually returns a jobid rather than the finished video, the required follow-up tool, and that it consumes the account's weekly Muse allowance (quota). That is real operational context the annotations cannot convey.

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?

Front-loaded with the action and its optional inputs, then the prompt conventions, then the async/waits behavior and cost, closing with the endpoint. No sentence is filler and the ordering matches how an agent would need the information.

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?

For a 17-parameter mutation tool with no output schema, the description covers the async job lifecycle, required follow-up call, and quota cost. It could say a bit more about failure/error handling or job-status semantics, but nothing essential for a correct call is missing.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds usage semantics the schema lacks: inputs must be referred to by name (image_1, video_1, audio_1…) inside the prompt, videos are typically passed 'to edit', and aspect ratio/spoken lines are prompt-level requirements. This is genuinely additive rather than a restatement.

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?

States a specific verb+resource ('Make one video with Muse from a prompt') and immediately scopes the optional input modalities, which is exactly what separates it from the sibling muse_generate_image. An agent can pick it without opening the schema.

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?

Gives clear invocation context: which asset id types to pass, that aspect ratio and spoken lines belong in the prompt, and that the follow-up path is muse_get_job (wait: true) after the ~50 s wait. It does not state when-not to use it (e.g. vs. muse_generate_image), so it stops short of full alternative routing.

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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