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Google Flow MCP

Google Flow MCP

by minhezluv
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

flow_create_scene

Create a new Google Flow scene from a prompt with character names, and assign it to a campaign or project for organized media generation.

Instructions

Create a new scene in Google Flow Scenes with characters and prompt.

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": {
      "prompt": "<prompt>"
    },
    "name": "flow_create_scene"
  }
}

Input Schema

NameRequiredDescriptionDefault
promptYesScene description/prompt.
campaignNoCampaign identifier for project matching (e.g., "ete-2026", "nouvelle-collection").
charactersNoCharacter names to include in the scene.
project_nameNoName for the project (will reuse existing project with same campaign, or create new).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the action without covering side effects, dependencies, project reuse logic, or what happens after creation. This is a minimal disclosure for a tool that likely creates persistent state.

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?

A single sentence that is front-loaded with the verb and resource. Every word earns its place, and there is no redundant fluff or repetition of schema details. This is an effective level of conciseness.

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

Completeness2/5

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

For a tool with 4 parameters and no output schema, the description provides no information about return values, error conditions, or how the creation process behaves (e.g., whether it creates a new project or reuses an existing one via campaign). The description is too sparse to be considered complete for an agent invocation.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The description mentions 'characters and prompt,' which is partially redundant with the schema, and adds no extra meaning beyond what the property descriptions already provide. The campaign and project_name parameters are not discussed in the description, but the schema covers them adequately.

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 uses a specific verb ('Create') and clearly identifies the resource ('a new scene in Google Flow Scenes'), with mention of characters and prompt. This distinguishes it from sibling tools like flow_create_character, which targets a different resource.

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

Usage Guidelines2/5

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

No context is provided about when to use this tool versus alternatives. The description only states what it does, without any mention of prerequisites, typical use cases, or exclusions relative to sibling tools like flow_create_character or flow_use_grid_architect.

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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