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xiaobenyang-com

bingcn

by xiaobenyang-com
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript

必应搜索工具

一个基于MCP协议的中文必应搜索工具，支持通过Claude等AI工具调用，无需API密钥即可获取网页内容。 A Chinese Bing search tool based on MCP protocol, which supports calling through AI tools such as Claude, and can obtain webpage content without API keys.## 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

bing_search

使用必应搜索指定的关键词，并返回搜索结果列表，包括标题、链接、摘要和ID

fetch_webpage

根据提供的ID获取对应网页的内容

检查服务 ## Inspector

工具在线测试： https://mcp.xiaobenyang.com/inspector/1777316659917827

Online Tool test https://mcp.xiaobenyang.com/inspector/1777316659917827

Related MCP server: Bing CN MCP Enhanced

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": {
    "必应搜索工具": {
      "headers": {
        "XBY-APIKEY": "<YOUR_XBY_APIKEY>"
      },
      "type": "sse",
      "url": "https://mcp.xiaobenyang.com/1777316659917827/sse"
    }
  }
}

STREAMABLE HTTP

{
  "mcpServers": {
    "必应搜索工具": {
      "headers": {
        "XBY-APIKEY": "<YOUR_XBY_APIKEY>"
      },
      "type": "streamable_http",
      "url": "https://mcp.xiaobenyang.com/1777316659917827/mcp"
    }
  }
}

STDIO

{
    "mcpServers": {
        "必应搜索工具": {
          "command": "npx",
          "args": [
            "-y",
            "xiaobenyang-mcp"
          ],
          "env": {
            "XBY_APIKEY": "<YOUR_XBY_APIKEY>",
            "mcpId": "1777316659917827",
          },
          "transport": "stdio"
        }
      }
}

Available Tools

2 tools
fetch_webpagefetch_webpageC

根据提供的ID获取对应网页的内容

ParametersJSON Schema
NameRequiredDescriptionDefault
result_idYes

TDQS

C2.7/5.0
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 of behavioral disclosure. It only states what the tool does (fetch content) without any additional behavioral traits, such as whether it's read-only, requires authentication, has rate limits, or what the output format might be. For a tool with no annotations, this leaves significant gaps in understanding its behavior.

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 concise and front-loaded in a single sentence: '根据提供的ID获取对应网页的内容'. It efficiently conveys the core purpose without unnecessary words. However, it could be slightly improved by adding minimal context, but it earns a high score for brevity and clarity within its limited scope.

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 complexity (a fetch operation with 1 parameter), no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't explain the return values, error handling, or any behavioral aspects. For a tool that likely involves network calls or data retrieval, more context is needed to be fully helpful to an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 1 parameter with 0% description coverage, and the description does not add any meaning beyond the schema. It mentions '提供的ID' (provided ID) but doesn't explain what 'result_id' represents, its format, or where it comes from. With low schema coverage, the description fails to compensate, leaving the parameter semantics unclear.

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 tool's purpose: '根据提供的ID获取对应网页的内容' (fetch the content of a webpage based on the provided ID). It specifies the verb '获取' (fetch/get) and the resource '网页的内容' (webpage content), making the action explicit. However, it doesn't differentiate from the sibling tool 'bing_search', which likely serves a different purpose (searching vs. fetching by ID), so it doesn't reach the highest score.

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 'bing_search' or any other context for usage, such as prerequisites or scenarios where this tool is preferred. The only implied usage is based on having a 'result_id', but this is not explicitly stated as a guideline.

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. 2 tool updatesv1.0.0
    • First observedbing_search
    • First observedfetch_webpage
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3.2/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: bing_search performs keyword searches and returns a list of results with metadata, while fetch_webpage retrieves the full content of a specific webpage based on an ID. There is no overlap in functionality, making it easy for an agent to select the correct tool for each task.

Naming Consistency5/5

Both tools follow a consistent verb_noun naming pattern: bing_search and fetch_webpage. The names are descriptive, use snake_case uniformly, and clearly indicate the action (search/fetch) and target (bing/webpage), providing predictability across the tool set.

Tool Count3/5

With only 2 tools, the set feels thin for a search and content retrieval server, as it lacks operations like filtering, pagination, or advanced search options. While the tools cover basic workflows, the count is borderline low for the apparent scope, potentially limiting agent capabilities.

Completeness3/5

The tools provide core search and content retrieval functions, but there are notable gaps: no ability to update, delete, or manage search results, and no support for operations like caching or result refinement. The surface is functional but incomplete for robust web search and content handling.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

Related MCP Connectors

Related MCP Servers

  • Bing CN MCP Enhanced

    Lynxe-public
    A
    license
    Not graded
    quality
    D
    maintenance
    An MCP server optimized for Chinese users that enables AI models to perform Bing searches and fetch webpage content without requiring an API key. It provides specialized tools for searching and scraping web data directly through supported AI environments like Claude or Cursor.
    41 npm
    6
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  • Kimi Coding MCP

    molicherry
    F
    license
    Not graded
    quality
    D
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    Wraps the Kimi Coding Search and Fetch APIs into MCP tools for web searching and content retrieval. It enables LLMs to perform targeted searches and crawl web pages using standardized interfaces.
    1
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