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Google Flow Agent MCP Server by useapi.net (third-party)

Get the agent's settings

flow_agent_get_settings
Read-onlyIdempotent

Read the agent settings of the account's agent project (or the projectId given): approval mode (ask: the agent asks before generating; auto: it generates without asking), project instructions (up to 3) and the default image and video model, aspect ratio and count. GET /agent/settings.

Input Schema

NameRequiredDescriptionDefault
emailNoThe Google Flow account email. Optional when the API token has one Flow account.
projectIdNoA Flow project id, instead of the account's own agent project ("My Agents Work <date>", made on its first chat).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is low; the description goes beyond them by disclosing the payload contents and decoding the 'ask' vs 'auto' approval-mode semantics, which the agent cannot get from annotations. It stops short of describing error or empty-settings behavior.

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?

Front-loaded with verb and resource, single dense sentence with every clause carrying information, plus the endpoint. Slightly heavy nesting of the approval-mode gloss, but nothing is wasted.

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?

With no output schema, the description carries the burden of describing the response and does so by enumerating every returned field group (approval mode, instructions, models, aspect ratio, count). Nothing an agent needs to call and interpret this read is missing.

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 coverage is 100% and both parameters are already documented there, including the projectId vs default-project distinction. The description's parenthetical ('or the projectId given') only mildly reinforces the schema, so baseline 3 is appropriate.

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?

Specific verb (read) plus specific resource (the agent settings of the account's agent project or a given projectId), and it enumerates exactly which settings are returned. An agent can distinguish it at a glance from the write sibling flow_agent_update_settings.

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?

The description gives clear context: read the account's default agent project, or supply projectId to target another project. It does not explicitly name flow_agent_update_settings as the mutation alternative or state exclusions, so it falls short of a 5.

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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