Ghibli Image Generator MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Ghibli Image Generator MCP ServerCreate a Ghibli-style image of a girl reading in a cozy library"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Ghibli Image Generator Api Open Ai 4O Image Generation Free MCP Server
用于访问 Ghibli Image Generator Api Open Ai 4O Image Generation Free API 的 MCP 服务器。
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🔍 搜索或找到本服务器(
bach-ghibli_image_generator_api_open_ai_4o_image_generation_free)🎉 点击 "安装 MCP" 按钮
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Related MCP server: MCP OpenAI Image Generation Server
简介
这是一个 MCP 服务器,用于访问 Ghibli Image Generator Api Open Ai 4O Image Generation Free API。
PyPI 包名:
bach-ghibli_image_generator_api_open_ai_4o_image_generation_free版本: 1.0.0
传输协议: stdio
安装
从 PyPI 安装:
pip install bach-ghibli_image_generator_api_open_ai_4o_image_generation_free从源码安装:
pip install -e .运行
方式 1: 使用 uvx(推荐,无需安装)
# 运行(uvx 会自动安装并运行)
uvx --from bach-ghibli_image_generator_api_open_ai_4o_image_generation_free bach_ghibli_image_generator_api_open_ai_4o_image_generation_free
# 或指定版本
uvx --from bach-ghibli_image_generator_api_open_ai_4o_image_generation_free@latest bach_ghibli_image_generator_api_open_ai_4o_image_generation_free方式 2: 直接运行(开发模式)
python server.py方式 3: 安装后作为命令运行
# 安装
pip install bach-ghibli_image_generator_api_open_ai_4o_image_generation_free
# 运行(命令名使用下划线)
bach_ghibli_image_generator_api_open_ai_4o_image_generation_free配置
API 认证
此 API 需要认证。请设置环境变量:
export API_KEY="your_api_key_here"环境变量
变量名 | 说明 | 必需 |
| API 密钥 | 是 |
| 不适用 | 否 |
| 不适用 | 否 |
在 Cursor 中使用
编辑 Cursor MCP 配置文件 ~/.cursor/mcp.json:
{
"mcpServers": {
"bach-ghibli_image_generator_api_open_ai_4o_image_generation_free": {
"command": "uvx",
"args": ["--from", "bach-ghibli_image_generator_api_open_ai_4o_image_generation_free", "bach_ghibli_image_generator_api_open_ai_4o_image_generation_free"],
"env": {
"API_KEY": "your_api_key_here"
}
}
}
}在 Claude Desktop 中使用
编辑 Claude Desktop 配置文件 claude_desktop_config.json:
{
"mcpServers": {
"bach-ghibli_image_generator_api_open_ai_4o_image_generation_free": {
"command": "uvx",
"args": ["--from", "bach-ghibli_image_generator_api_open_ai_4o_image_generation_free", "bach_ghibli_image_generator_api_open_ai_4o_image_generation_free"],
"env": {
"API_KEY": "your_api_key_here"
}
}
}
}可用工具
此服务器提供以下工具:
ghibli_generate_image
Ghibli generate
端点: POST /generateghibliimage.php
example_response
example response
端点: POST /ghibliresponse.php
技术栈
传输协议: stdio
HTTP 客户端: httpx
许可证
MIT License - 详见 LICENSE 文件。
开发
此服务器由 API-to-MCP 工具生成。
版本: 1.0.0
Available Tools
2 toolsexample_responseD
example response
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description 'example response' gives no insight into whether the tool is read-only, destructive, requires authentication, has rate limits, or any other behavioral traits. It fails to provide any useful context beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is extremely concise with just two words, it is under-specified rather than efficiently informative. The brevity does not serve clarity or utility, as it fails to convey any meaningful content about the tool's function or use.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, output schema, and a vague description, the description is completely inadequate for understanding the tool. It provides no context about complexity, behavior, or expected outcomes, making it insufficient for agent decision-making despite the simple parameterless schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description does not add any parameter information, which is acceptable given the baseline of 4 for zero parameters, as no compensation is needed for missing details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'example response' is a tautology that merely restates the tool name 'example_response' without providing any meaningful information about what the tool does. It lacks a specific verb, resource, or any indication of functionality, making it completely unhelpful for understanding the tool's purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool, what context it applies to, or how it differs from the sibling tool 'ghibli_generate_image'. There is no mention of alternatives, prerequisites, or exclusions, leaving the agent with no usage information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ghibli_generate_imageD
Ghibli generate
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure but offers none. 'Ghibli generate' doesn't indicate whether this is a read or write operation, what permissions might be needed, whether it has side effects, rate limits, or what the output format might be. For a generation tool with zero annotation coverage, this is a critical gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
While extremely brief ('Ghibli generate'), this isn't true conciseness but rather under-specification. The two words don't form a complete thought and fail to convey necessary information. Every sentence should earn its place, but here the minimal content doesn't justify its existence as a helpful description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of an image generation tool with no annotations and no output schema, the description is completely inadequate. It doesn't explain what 'Ghibli' means, what kind of image is generated, what the output looks like, or any behavioral characteristics. The description fails to provide the minimal context needed for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters (schema coverage 100%), so there's no need for parameter documentation in the description. The baseline for zero parameters is 4, as the description doesn't need to compensate for any parameter gaps. However, it doesn't reach 5 because it could optionally mention that no inputs are required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Ghibli generate' is a tautology that essentially restates the tool name 'ghibli_generate_image' with minimal added meaning. It doesn't specify what resource is being generated (presumably an image based on the name) or what 'Ghibli' refers to (likely Studio Ghibli style). While it hints at generation, it lacks the specific verb+resource clarity needed for proper understanding.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of context, prerequisites, or comparison with the sibling tool 'example_response'. Users must infer usage entirely from the tool name, which is insufficient for effective tool selection.
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.
2 tool updates
v1.0.0- First observed
example_response - First observed
ghibli_generate_image
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: 'example_response' appears to provide sample outputs or documentation, while 'ghibli_generate_image' performs the core image generation function. There is no overlap or ambiguity between these tools.
The naming is inconsistent: 'example_response' uses snake_case but lacks a clear verb-action pattern, while 'ghibli_generate_image' uses snake_case with a more descriptive verb-noun structure. This mixed approach reduces predictability.
With only 2 tools, this server feels under-scoped for an image generator domain. A typical image generation service would include tools for configuration, style control, or batch operations, making this count insufficient for robust functionality.
The toolset is severely incomplete for an image generator: it lacks essential operations like parameter adjustment, style selection, image editing, or retrieval of generated images. The 'example_response' tool does not contribute to core functionality, leaving major gaps.
Maintenance
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