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AceDataCloud

SeedreamMCP

by AceDataCloud
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

List Seedream models

seedream_list_models
Read-onlyIdempotent

Retrieve a formatted table of all available Seedream models, including capabilities and pricing, to compare options and choose the right model for image generation or editing tasks.

Instructions

List all available Seedream models with their capabilities and pricing.

Use this when:
- User asks what models are available
- You need to help choose the right model for a task
- You want to compare model capabilities

Returns:
    Formatted table of all Seedream models with descriptions.

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.5
  2. Removedv0.1.3
  3. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered by structured data. The description's only addition is the return shape (a formatted table), which partly duplicates the output schema and says nothing about caching, rate limits, or ordering.

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?

Purpose sentence is front-loaded and the bullets are scannable and short. The trailing 'Returns' block is largely redundant given an output schema exists, so the text is not maximally economical.

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 catalog call with an output schema and full annotation coverage, the description supplies everything an agent needs to decide to call it. The only shortfall is not stating that results are exhaustive/static, which would help an agent avoid redundant calls.

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 no parameters, so the baseline of 4 applies; there is nothing for the description to disambiguate. No misleading parameter language is 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+resource ('List all available Seedream models') and enumerates the payload (capabilities and pricing), which cleanly separates it from the generate/edit/decompose siblings.

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?

Three explicit 'use this when' bullets give clear triggering conditions (user asks what's available, model selection help, capability comparison). It does not name an alternative sibling or state when not to use it, but for a zero-arg catalog tool the alternatives are obvious.

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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