A
licenseD
qualityD
maintenanceA Model Context Protocol server that enables searching for similar images by text description, integrating Inspire's backend image search capabilities with LLM interfaces like Claude Desktop.
1
3
GPL 3.0
Pixabay MCP Server
by zym9863
pixabay-mcp MCP 服务器
用于 Pixabay 图像搜索的模型上下文协议服务器
这是一个基于 TypeScript 的 MCP 服务器，提供对 Pixabay 图片 API 的访问。它通过以下方式演示了 MCP 的核心概念：
在 Pixabay 上搜索图片的工具
带有图像 URL 和元数据的格式化结果
API 请求的错误处理
特征
工具
search_pixabay_images- 在 Pixabay 上搜索图片将搜索查询作为必需参数
图像类型、方向和每页结果的可选参数
返回带有 URL 的格式化图像结果列表
配置
需要将 Pixabay API 密钥设置为环境变量
PIXABAY_API_KEY默认启用安全搜索
API 问题和无效参数的错误处理
Related MCP server: Lorem Ipsum MCP Server
发展
安装依赖项：
npm install构建服务器：
npm run build对于使用自动重建的开发：
npm run watch安装
将您的 Pixabay API 密钥设置为环境变量：
# On Windows
set PIXABAY_API_KEY=your_api_key_here
# On macOS/Linux
export PIXABAY_API_KEY=your_api_key_here要与 Claude Desktop 一起使用，请添加服务器配置：
在 MacOS 上： ~/Library/Application Support/Claude/claude_desktop_config.json在 Windows 上： %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"pixabay-mcp": {
"command": "/path/to/pixabay-mcp/build/index.js",
"env": {
"PIXABAY_API_KEY": "your_api_key_here"
}
}
}
}调试
由于 MCP 服务器通过 stdio 进行通信，调试起来可能比较困难。我们推荐使用MCP Inspector ，它以包脚本的形式提供：
npm run inspector检查器将提供一个 URL 来访问浏览器中的调试工具。
Available Tools
2 toolssearch_pixabay_imagesC
Search for images on Pixabay
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search query terms | |
| image_type | No | Filter results by image type | all |
| orientation | No | Filter results by image orientation | all |
| per_page | No | Number of results per page (3-200) |
TDQS
C2.9/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Search for') but doesn't describe any behavioral traits such as rate limits, authentication needs, pagination behavior, or what the response looks like. For a search tool with zero annotation coverage, this leaves significant gaps in understanding how it operates.
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 a single, efficient sentence that directly states the tool's purpose without any unnecessary words. It's appropriately sized and front-loaded, making it easy to understand at a glance. Every word earns its place.
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?
Given the lack of annotations and output schema, the description is incomplete for a search tool with 4 parameters. It doesn't cover behavioral aspects like response format, error handling, or usage constraints. While the schema handles parameters well, the overall context for proper tool invocation is insufficient.
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?
The input schema has 100% description coverage, with all parameters well-documented in the schema itself. The description doesn't add any meaning beyond what the schema provides—it doesn't explain parameter interactions, default behaviors, or usage examples. This meets the baseline of 3 since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Search for') and resource ('images on Pixabay'), making the purpose immediately understandable. It distinguishes from the sibling tool 'search_pixabay_videos' by specifying images, though it doesn't explicitly contrast them. The description is specific but lacks explicit sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention the sibling tool 'search_pixabay_videos' or any other potential alternatives, nor does it provide context about appropriate use cases or exclusions. The user must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_pixabay_videosC
Search for videos on Pixabay
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search query terms | |
| video_type | No | Filter results by video type | all |
| orientation | No | Filter results by video orientation | all |
| per_page | No | Number of results per page (3-200) | |
| min_duration | No | Minimum video duration in seconds | |
| max_duration | No | Maximum video duration in seconds |
TDQS
C2.9/5.0
Behavior2/5
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 only states the basic action. It doesn't mention authentication requirements, rate limits, pagination behavior, error handling, or what the search results look like (e.g., format, fields). For a search tool with no annotations, this leaves significant gaps in understanding how it behaves.
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 a single, efficient sentence with no wasted words, making it easy to parse and front-loaded with the core purpose. It's appropriately sized for a straightforward search tool.
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?
Given the tool's complexity (6 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral traits, output format, and usage context, making it insufficient for an agent to fully understand how to invoke and interpret results without relying heavily on the schema alone.
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?
The description adds no parameter-specific information beyond what's in the input schema, which has 100% coverage with detailed descriptions for all 6 parameters. Since the schema fully documents parameters, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Search for') and resource ('videos on Pixabay'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from its sibling tool 'search_pixabay_images' beyond the resource type, which is implied but not stated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, such as its sibling 'search_pixabay_images' for image searches. There's no mention of prerequisites, context, or exclusions, leaving usage entirely to inference from the tool name and parameters.
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 tool update
v1.0.0- Added
search_pixabay_videos
1 tool update
- First observed
search_pixabay_images
TDQS
B3.2/5.0
Scored across 2 tools
Disambiguation5/5
The two tools have perfectly distinct purposes: one searches for images and the other searches for videos on Pixabay. There is no overlap or ambiguity between them, making it trivial for an agent to choose the correct tool based on the desired media type.
Naming Consistency5/5
Both tools follow a consistent verb_noun pattern with 'search_pixabay_' as a prefix, followed by the media type ('images' or 'videos'). This naming convention is clear, predictable, and uniform across all tools in the set.
Tool Count3/5
With only two tools, the server feels thin for a media search domain, as it lacks operations for retrieving details, downloading, or managing favorites. However, it is reasonable for a minimal search-focused interface, though agents might need workarounds for extended functionality.
Completeness2/5
The tool set is severely incomplete for a Pixabay integration, covering only search operations. There are significant gaps, such as no tools for getting image/video details, downloading media, or handling user accounts, which limits agent workflows and could lead to failures in broader tasks.
Maintenance
ActivityInactive
ResponsivenessNo issues
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