Skip to main content
Glama
156554395

image-video-generation-mcp

by 156554395

batch_generate_images

Generate multiple images from multiple prompts in parallel batches. Supports up to 100 prompts with configurable model, size, quality, and batch management.

Instructions

批量生成多张图像,支持并行处理和批次管理

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptsYes提示词数组,最多支持100个
modelNo使用的模型 (cogview-4, cogview-4-250304, cogview-3-flash)
qualityNo图像质量standard
sizeNo图像尺寸 (例如: 1024x1024, 1024x1792)1024x1024
watermark_enabledNo是否添加水印
user_idNo用户ID,用于跟踪 (6-128个字符)
batch_sizeNo每批处理的提示词数量
parallelNo是否并行处理批次内的请求
max_concurrentNo并行处理时的最大并发数
delay_between_batchesNo批次间的延迟时间(毫秒)
Behavior2/5

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

No annotations provided, so description carries full burden. It mentions parallel processing and batch management but does not disclose error handling, rate limits, idempotency, or other behavioral traits. The description is too brief to adequately inform the agent.

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?

The description is a single sentence, concise and front-loaded. However, it is in Chinese, which may reduce clarity for English-speaking agents. Still, it earns its place without waste.

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?

With 10 parameters, no output schema, and no annotations, the description is insufficient. It does not explain return format, error states, or how batch results are returned. More detail is needed for a tool of this complexity.

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%, so parameters are already documented. The description adds minimal value, only hinting at parallel and batch parameters. Since coverage is high, baseline is 3, and the description does not go beyond that.

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 clearly states the action '批量生成多张图像' (batch generate multiple images) and mentions key capabilities like parallel processing and batch management, distinguishing it from siblings like generate_image (single image) and generate_video.

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?

No explicit guidance on when to use this tool versus alternatives. The name implies batch processing, but the description lacks when/when-not advice. Sibling names provide some implicit distinction but the description itself does not.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/156554395/image-video-generation-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server