Feeling Search — Art Style Reference & Prompt Encyclopedia

cloud.xiximm由 xiximm.cloud 发布官方发布者v0.2.6更新于 Oct 30, 2026

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

已验证Streamable HTTP可网页运行知识与记忆媒体与设计

概览

AI 生成的概览

把一句口语描述转换成匹配的视觉艺术风格及其背后的感受词,可用本地词典与语义引擎,也可用远端端点。

可以做什么
  • 把一句话解析成感受词与排序后的视觉风格,并标明结果来自哪一层
  • 查询单个感受词:落在哪些风格、对立词、常共现词、是否为标识词
  • 列出全部感受词表,或带定义与规模的风格集合
  • 取单个风格的完整信息:定义、生成提示词、词集、年代地域与参考图地址
  • 查看词表版本、规模以及是否配置了云端额度
适用场景
适合把情绪或场景描述转成具体的艺术风格参考与提示词词汇,用于插画、设计或图像生成需求。本地包适合离线、注重隐私的使用;远端端点可免去下载。
运行要求
需要 npm 包 feeling-search-mcp(用 npx 运行,首次会下载约 21 MB 的词典与引擎),或使用远端 streamable HTTP 端点。无需账号或 API 密钥。可选配置包括 FS_MCP_URL 或 --endpoint、用于受限端点的 FS_MCP_TOKEN、--timeout、--remote 与 FS_DATA_ROOT。
安装前请注意
工具默认只读且免费,但云端兜底路径被描述为按次付费,且仅在明确允许时才会调用;未配置 FS_QUOTA 时应如实说明需要付费额度,而不是假装成功。远端端点会把文本发送到外部,本地包则不会。标为占位图的图片不应作为风格样本引用。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Feeling Search — Art Style Reference & Prompt Encyclopedia,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/cloud.xiximm%2Ffeeling-search/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "mcpServers": {
    "feeling-search-art-style-reference-promp": {
      "type": "http",
      "url": "https://xiximm.cloud/mcp"
    }
  }
}

README

feeling-search-mcp

MCP server for feeling-search — turn one colloquial sentence into the visual style that matches it best, plus the feeling words that led there. Every style carries its name, a one-line definition and the words that triggered it.

A commercial-grade art reference chart, art-style encyclopedia and art-style AI prompt dictionary, exposed over the Model Context Protocol.

"下雨天一个人走在便利店门口,冷白灯光"   → 感受词:星光 / 窗光 / 冷光 …   → 视觉风格:垂直式哥特 / 星图 / 托莱多画派 …

Install

Two shapes. Neither needs an account or an API key.

Local (default, recommended) — the package now ships the whole thing: 762-word lexicon, the 598-style index, and both semantic engines. It runs offline.

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

First npx run downloads ~21 MB (the two engines are 8 MB zh + 10 MB en). After that: lexicon hits answer in ~10 ms, whole-sentence queries in ~25 ms, all on your machine.

Remote (no download) — point the client at the endpoint:

json
{  "mcpServers": {    "feeling-search": {      "type": "streamableHttp",      "url": "https://xiximm.cloud/mcp"    }  }}

Or keep the local install but forward: npx feeling-search-mcp --remote. Remote answers in 0.76–1.64 s (network round trip + cold start), local in 10–90 ms, and local never sends your text anywhere.

Machine-readable copy of both variants: mcp.json.

Tools

ToolWhat it doesCost
word_analyzeOne sentence → the best-matching visual styles + the feeling words behind them. source tells you which layer answered (local lexicon / engine semantic model / cloud fallback)free, offline
word_lookupLook up a single feeling word: definition, near-synonyms, landing stylesfree
word_listBrowse / search the full feeling-word lexiconfree
style_getOne style in full: definition, parent style, member words, reference imagesfree
word_statusLexicon version, coverage — use it to check the data is freshfree

Every tool is read-only and costs nothing. The paid /v2/analyze cloud path is off by default on the public endpoint and only runs when a caller explicitly opts in.

Pricing status (2026-10-28): everything is free — no API key, no quota token. The upstream service runs free by default; paid 402 / x402 is only enabled if the operator explicitly sets FS_PAID=1. Only rate limits apply: 20 requests/minute per IP, and POST /v2/analyze is capped at 200 calls per visitor per day. Nothing in this bridge needs to change either way.

Want to know how much traffic the lexicon is getting? The upstream exposes a public GET /v2/stats telemetry endpoint (page views, unique visitors, referrers, AI crawler hits, no personal data) — see https://xiximm.cloud/docs/api.html.

Two layers, and which one answers

word_analyze only escalates when it has to:

LayerWhen it runsLatencyWhat it returns
Lexicon (source: "local")The sentence contains 2+ lexicon words~10 msExact feeling words, each with its landing styles
Semantic engine (source: "engine")The lexicon hits 0–1 words — i.e. it didn't really understand the sentence~25 msReal words from the 762-entry lexicon (cosine against 762 word vectors) + styles ranked against 598 style vectors
Cloud (source: "cloud")Only on the remote endpoint, and only with allow_cloud: true0.8–1.6 sPaid fallback

Two engines, picked by language:

  • Chinese — ask in whole Chinese sentences. Any Han character makes it the Chinese engine; don't mix, e.g. 有点 lonely 的雨夜 gets shredded by the Chinese tokenizer.
  • English — ask in whole English sentences. moody rainy night in old Hong Kong.
  • Force one with lang: "zh" | "en"; default is auto.

Negation is computed outside the model and is deterministic: 不要压抑 drops 压抑 and demotes every style that carries it, on both layers.

What's in the package

PathSizeWhy
data/src/words.json, data/standards/*.json~2 MBLexicon, 598 styles, aliases, version
data/standards/zh-engine/8.1 MBChinese ternary engine (wasm core + weights)
data/standards/ternlight/9.8 MBEnglish engine (wasm, weights embedded)
data/standards/idx/0.9 MB598 style vectors, per language, int8
lib/<100 KBTool definitions, engine loader, lexicon

Everything is generated from the upstream repo by deploy/pack-mcp.mjs, which also runs a --check drift comparison — the package can't silently fall behind the data.

Endpoint

PropertyValue
TransportStreamable HTTP (sse also accepted)
URLhttps://xiximm.cloud/mcp
Authnone — anonymous initialize and tools/list both succeed
Tools5 (word_analyze, word_lookup, word_list, style_get, word_status)
npm packagefeeling-search-mcp
MCP Registry namecloud.xiximm/feeling-search

Configuration

Env / flagDefaultMeaning
FS_MCP_URL / --endpointhttps://xiximm.cloud/mcpEndpoint to bridge to
FS_MCP_TOKENunsetSent as Authorization: Bearer <token> when the endpoint is gated
--timeout30000Per-request timeout in ms
--remoteoffForward to the endpoint instead of running locally
--data <dir> / FS_DATA_ROOTpackage data/Where the lexicon and engines live

stdout carries protocol messages only; all diagnostics go to stderr.

Reach & traffic

One command checks every channel this package is listed on — npm downloads, GitHub traffic and referrers, MCP Registry versions, directory availability, and open PRs:

bash
node scripts/traffic.mjs          # human-readable reportnode scripts/traffic.mjs --json   # machine-readable, for diffing over time

Requires the gh CLI to be logged in (GitHub traffic needs push permission on the repo). Mind the reporting lag: npm download stats appear 24–48h after the first publish, and GitHub traffic only covers the last 14 days.

referrers is the useful signal for directories — it shows which registry actually sends visitors. Directory sites themselves publish no view counts.

Related

License

MIT

来源:README.md,提交 7a6aedf

工具

5

word_analyze

把一句描述解析成词与风格

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。

输入参数langtext必填quotawordsstylesallow_cloud

word_lookup

查一个词落在哪些风格

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。

输入参数word必填

word_list

枚举感受词或视觉风格

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。

输入参数kind

style_get

取单个风格的定义与对应图片

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。

输入参数id必填

word_status

查看词表版本与云端额度状态

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。

无需输入参数。

版本历史

2
  1. v0.2.6最新Oct 30, 2026
  2. v0.2.4Oct 29, 2026

评分

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  • 近 30 天内可连通必需25 分
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  • 描述必需15 分
  • 图标10 分
  • 文档15 分
  • 许可证10 分

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