Wikimedia-Search-Images
Enables searching for images on Wikimedia Commons with detailed metadata including download URLs, and provides optional thumbnail combinations for visual comparison.
Click on "Install 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., "@Wikimedia-Search-Imagesfind images of the Eiffel Tower at night"
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.
Wikimedia图片搜索服务 Wikimedia Search Images
该MCP服务器使AI助手能够在Wikimedia Commons上搜索图片,提供详细的元数据和可选的缩略图组合,帮助AI模型进行视觉比较。 This MCP server enables AI assistants to search for images on Wikimedia Commons, providing detailed metadata and optional thumbnail combinations to assist AI models in visual comparisons.## 工具列表 Tool List
本MCP服务封装下列工具,可让模型通过标准化接口调用以下功能。 本MCP服务封装下列工具,可让模型通过标准化接口调用以下功能。
工具 Tool | 描述 Description |
wikimedia_search_images | Search for images on Wikimedia Commons with metadata including download URLs and optional thumbnail composite image for visual comparison. Use results to e.g. fetch full images that are relevant for your task. |
检查服务 ## Inspector
工具在线测试: https://mcp.xiaobenyang.com/inspector/1777316659355651
Online Tool test https://mcp.xiaobenyang.com/inspector/1777316659355651
Related MCP server: MCP Image Resolver
服务配置 MCP Server Config
如何获取 XBY-APIKEY ? How to get XBY-APIKEY ?
访问小笨羊科技网站 https://xiaobenyang.com,注册用户即可获得APIKEY Visit XiaoBenYang website https://xiaobenyang.com, register and get the APIKEY.
SSE
{
"mcpServers": {
"Wikimedia图片搜索服务": {
"headers": {
"XBY-APIKEY": "<YOUR_XBY_APIKEY>"
},
"type": "sse",
"url": "https://mcp.xiaobenyang.com/1777316659355651/sse"
}
}
}STREAMABLE HTTP
{
"mcpServers": {
"Wikimedia图片搜索服务": {
"headers": {
"XBY-APIKEY": "<YOUR_XBY_APIKEY>"
},
"type": "streamable_http",
"url": "https://mcp.xiaobenyang.com/1777316659355651/mcp"
}
}
}STDIO
{
"mcpServers": {
"Wikimedia图片搜索服务": {
"command": "npx",
"args": [
"-y",
"xiaobenyang-mcp"
],
"env": {
"XBY_APIKEY": "<YOUR_XBY_APIKEY>",
"mcpId": "1777316659355651",
},
"transport": "stdio"
}
}
}
Available Tools
1 toolwikimedia_search_imageswikimedia_search_imagesC
Search for images on Wikimedia Commons with metadata including download URLs and optional thumbnail composite image for visual comparison. Use results to e.g. fetch full images that are relevant for your task.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| limit | No | ||
| offset | No | ||
| license | No | ||
| include_thumbnails | No |
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. It mentions that results include 'metadata including download URLs and optional thumbnail composite image,' which gives some insight into outputs. However, it fails to disclose critical behavioral traits such as rate limits, authentication requirements, pagination behavior (beyond offset/limit parameters), error conditions, or whether this is a read-only operation. For a search tool with no annotation coverage, this leaves significant gaps.
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?
The description is concise and well-structured in two sentences. The first sentence front-loads the core functionality, and the second provides a usage example. There is no wasted verbiage, and each sentence adds value, though it could be slightly more detailed without losing efficiency.
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 (5 parameters, no annotations, no output schema), the description is incomplete. It lacks parameter explanations, detailed behavioral context (e.g., rate limits, errors), and output specifics. While it covers the basic purpose and a usage hint, it doesn't provide enough information for an agent to confidently invoke the tool without guessing about parameters or behavior.
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?
Schema description coverage is 0%, meaning none of the 5 parameters have descriptions in the schema. The tool description does not explain any parameters—it doesn't mention 'query,' 'limit,' 'offset,' 'license,' or 'include_thumbnails,' nor does it clarify their purposes, formats, or constraints. With low coverage and no compensation in the description, this falls short of the baseline expectation.
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 clearly states the tool's purpose: 'Search for images on Wikimedia Commons with metadata including download URLs and optional thumbnail composite image for visual comparison.' It specifies the verb ('Search'), resource ('images on Wikimedia Commons'), and key outputs (metadata, download URLs, thumbnails). However, without sibling tools, it cannot demonstrate differentiation from alternatives, preventing a perfect score.
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 implied usage guidance: 'Use results to e.g. fetch full images that are relevant for your task.' This suggests a workflow where this tool is used for discovery before fetching images. However, it lacks explicit when-to-use rules, prerequisites, or comparisons to alternatives (none exist here), making it adequate but not comprehensive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined as searching for images on Wikimedia Commons with metadata and optional thumbnails.
The single tool name 'wikimedia_search_images' follows a consistent verb_noun pattern, using snake_case and clearly indicating the action (search) and target (images). There are no other tools to compare against, so consistency is inherently perfect.
A single tool is too few for a server named 'Wikimedia-Search-Images', which suggests a broader scope for image-related operations. While the tool covers search well, the lack of additional tools (e.g., for fetching, filtering, or managing images) makes the set feel incomplete and limited in functionality.
The tool set is severely incomplete for the implied domain of Wikimedia image operations. It only provides search functionality, with no tools for actions like downloading full images, viewing metadata details, or handling image collections, leaving significant gaps that could hinder agent workflows.
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