MCP MeasureMCP Measure

index observed

Feeling Search — Art Style Reference & Prompt Encyclopedia

One sentence in, the best-matching visual style out: art reference chart and prompt encyclopedia.

Should I use this

Quality & Safety

B
Description quality
52%
Schema completeness
84%
Naming quality
80%
Poisoning risk
80%
Permission match
100%
Protocol compliance
100%

Findings (7)

  • HIGHTool poisoning patterns detected
  • MEDIUMTool 'style_get' description contains placeholder textin style_get
  • LOWTool 'word_analyze' description lacks action verbin word_analyze
  • LOWTool 'word_lookup' description lacks action verbin word_lookup
  • LOWTool 'style_get' description lacks action verbin style_get
  • LOWTool 'word_status' description lacks action verbin word_status
  • INFOTool description contains placeholder or incomplete textin style_get

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~872Tokens (tool definitions)
~680 BTypical response size
Moderate attention impact (0.68% of 128k context)

This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.

Install

One-Click Install

Add this to your `claude_desktop_config.json` file:

{
  "mcpServers": {
    "feeling-search": {
      "command": "npx",
      "args": [
        "feeling-search-mcp"
      ]
    }
  }
}

Runnable packages

npmfeeling-search-mcp0.1.2stdio

Remote endpoints

https://xiximm.cloud/mcpstreamable-http

What it can do

Tool inventory

Tools (5)

🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
🟢word_analyze(text, words, styles, allow_cloud, quota)

把一句中文/英文口语描述解析成感受词与视觉风格。默认纯本地词典（免费、不联网）；本地一个词都没命中且允许时，才上云。返回 score 是相对值不是概率，styles[].matched 是可以直接引用给用户看的命中词。

Input Schema

{
  "type": "object",
  "properties": {
    "text": {
      "type": "string",
      "minLength": 1,
      "maxLength": 500,
      "description": "要解析的描述，最长 500 字"
    },
    "words": {
      "type": "integer",
      "minimum": 1,
      "maximum": 12,
      "default": 6,
      "description": "返回几个感受词"
    },
    "styles": {
      "type": "integer",
      "minimum": 0,
      "maximum": 20,
      "default": 5,
      "description": "返回几个视觉风格"
    },
    "allow_cloud": {
      "type": "boolean",
      "default": false,
      "description": "本地零命中时是否允许上云（远端默认关闭；显式传 true 才会消耗额度）"
    },
    "quota": {
      "type": "string",
      "maxLength": 256,
      "description": "已购额度令牌（响应头 X-FS-Quota 的值）。本机也可用环境变量 FS_QUOTA；远端 MCP 客户端没法设环境变量，就用这个参数"
    }
  },
  "required": [
    "text"
  ],
  "additionalProperties": false
}
🟢word_lookup(word)

查一个感受词：落在哪些风格、对立词是什么、常一起出现的词、是否标识词。纯本地查表。

Input Schema

{
  "type": "object",
  "properties": {
    "word": {
      "type": "string",
      "minLength": 1,
      "maxLength": 30,
      "description": "要查的词，如「留白」「枯淡」"
    }
  },
  "required": [
    "word"
  ],
  "additionalProperties": false
}
🟢word_list(kind)

列出全部感受词（带共享度）或视觉风格（带定义与词集规模）。调 analyze 之前先拉一次可避免名字拼错。

Input Schema

{
  "type": "object",
  "properties": {
    "kind": {
      "type": "string",
      "enum": [
        "words",
        "styles"
      ],
      "default": "words",
      "description": "枚举哪一类"
    }
  },
  "additionalProperties": false
}
🟢style_get(id)

按风格 id（或中文名）取一个风格：定义、生成用提示词、感受词、年代地域，以及它对应的图片（thumb 320 / full 960 绝对地址，带 kind/credit/license）。kind=work 是有出处的真作品，synthetic 是 AI 示意，placeholder 是占位图。

Input Schema

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "minLength": 1,
      "maxLength": 64,
      "description": "风格 id（如 synthwave）或中文名（如 合成器波）"
    }
  },
  "required": [
    "id"
  ],
  "additionalProperties": false
}
🟢word_status

返回词表版本、规模（词/风格/变种/挂靠率）以及是否配置了云端额度。

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}

Community

Rate this Server

Evidence

Recent observations

verifiedversion not recorded5 tools