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kira4094

Agnes Image MCP Server

by kira4094

Agnes Image MCP Server

MCP server for Agnes Image 2.1 Flash (text-to-image generation), connected via OpenAI-compatible API.

Features

  • Generate images from text prompts

  • Supports aspect ratios (1:1, 16:9, 9:16, 4:3, 3:4, etc.)

  • Custom resolution (1K~4K)

  • Multi-image generation

  • Returns clickable image URLs

Related MCP server: Gemini Flash Image MCP Server

Requirements

Install

cd agnes-image-mcp-server
npm install
npm start

Environment Variables

Variable

Required

Default

Description

AGNES_API_KEY

Your Agnes AI API key

AGNES_MODEL

agnes-image-2.1-flash

Model name

AGNES_BASE_URL

https://apihub.agnes-ai.com/v1

API base URL

CC-Switch / Claude Code Config

{
  "mcpServers": {
    "agnes-image": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@kira4094/agnes-image-mcp-server"],
      "env": {
        "AGNES_API_KEY": "your-agnes-api-key"
      }
    }
  }
}

Tool: agnes_image_generate

Parameter

Type

Required

Description

prompt

string

Text description (Chinese/English)

size

string

Resolution (1024x1024, 1024x768, 768x1024)

ratio

string

Aspect ratio (1:1, 16:9, 9:16, 4:3, 3:4, etc.)

n

number

Number of images (default 1)

License

MIT

Available Tools

1 tool
agnes_image_generateB

Generate an image using Agnes Image 2.1 Flash (text-to-image model). Supports OpenAI-compatible API at https://apihub.agnes-ai.com/v1. Excels at: creative illustration, concept art, UI mockups, photorealistic renders, Chinese-style art.

ParametersJSON Schema
NameRequiredDescriptionDefault
nNoNumber of images to generate
sizeNoImage resolution (if set, ratio is ignored). Supports 1K~4K tiers. Use 2048x2048 for 2K.1024x1024
ratioNoAspect ratio (ignored if size is set)1:1
promptYesText description of the image to generate. Supports Chinese and English.

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions the model version and API compatibility, but does not disclose important behavioral aspects such as output format (e.g., returned image URL or base64), authentication requirements, rate limits, or error behavior.

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?

The description is very concise, consisting of three sentences that front-load the primary action. Every sentence adds value—introducing the model, noting API compatibility, and listing strengths—with no unnecessary fluff.

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 no output schema and no annotations, the description should explain what the tool returns and any operational constraints. It lacks information about the response format, required API keys, or typical usage context beyond the listed strengths, leaving significant gaps.

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%, with each parameter already having a description. The tool description adds no additional parameter meaning beyond what the schema provides, so the baseline score of 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?

The description clearly states the tool's function: 'Generate an image using Agnes Image 2.1 Flash (text-to-image model).' It uses a specific verb and resource, and even lists example use cases, making the purpose unambiguous.

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?

The description implies when to use the tool by listing 'Excels at: creative illustration, concept art, UI mockups, photorealistic renders, Chinese-style art.' However, it does not provide explicit when-to-use or when-not-to-use guidance, and there are no sibling tools to contrast with.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev1.0.3
    • First observedagnes_image_generate

TDQS

A3.7/5.0

Scored across 1 tool

Disambiguation5/5

Only one tool exists, so there is no possibility of confusion or overlap. The tool's purpose is unmistakable.

Naming Consistency4/5

The single tool name 'agnes_image_generate' is clear and follows a consistent object-verb structure, though the typical verb-noun order is reversed. Since there is only one tool, the pattern is internally consistent.

Tool Count3/5

With exactly one tool, the server is minimal but appropriately scoped for a dedicated image generation service. It feels thin but not unreasonable for such a focused purpose.

Completeness5/5

The server's stated purpose is text-to-image generation, and the single tool fully covers that operation. There are no obvious gaps within the narrow domain, as additional features like editing or listing would be outside the stated scope.

Maintenance

ActivityInactive
ResponsivenessNo issues

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