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GoogleFlow_MCP

GoogleFlow_MCP

by marvicqui
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

List available video/image models

flow_list_models
Read-only

Lists the Veo and image model IDs your API key can use plus this server's configured defaults, helping you choose valid models for generation.

Instructions

List the Veo / image model ids your API key can use, plus the defaults this server is configured with.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "flow_list_models"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description adds real context beyond that: results are scoped to the caller's API key and also expose the server's configured defaults. It stops short of noting rate limits or whether the list can change over time, but it meaningfully exceeds the annotation.

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 with no filler, leading with the verb and the resource. Every clause (key scoping, defaults) adds distinct 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 zero-parameter, read-only discovery tool with no output schema, the description conveys enough about what comes back (model ids plus defaults). A small gap remains: it does not say whether the defaults are a separate field or embedded per model entry, which matters slightly with no output schema to consult.

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 tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a parameterless tool applies. No misleading parameter claims are present.

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 (list) and a precise resource (Veo / image model ids), and adds the scope qualifier 'your API key can use' plus the server-configured defaults. It is unmistakably distinct from the generation/asset siblings, which return media rather than model metadata.

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?

Usage is only implied: an agent can infer this is a discovery call to run before generating video or images. There is no explicit 'call this first' directive and no statement of when not to use it versus flow_list_assets, so guidance stays at the implied level.

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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