io.github.zhiyu-dev由 GitHub 账号 zhiyu-dev 发布v1.1.0更新于 Oct 24, 2026
Affect analysis, 3D avatar params, empathy hints and somatic emotion decode.
Chenji Affect 是一个远程 MCP 服务器，把文本转换为结构化情感信号：情绪向量、虚拟形象动画参数、共情策略与身体感受解码。
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。
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/io.github.zhiyu-dev%2Fchenji-affect-mcp/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。把它添加到你客户端的 mcpServers 配置中。
{
"mcpServers": {
"chenji-affect": {
"type": "http",
"url": "https://taichusjs.cn/mcp",
"headers": {
"x-api-key": "<YOUR_API_KEY>"
}
}
}
}Turn raw text into structured affect signals — an 8-dimensional emotion vector, emotion texture labels, causal intent, 3D avatar driving parameters, empathy response strategies, and somatic-sensation emotion decoding — inside any MCP-capable client (Claude Desktop, Cursor, Qoder, etc.).
Powered by the Chenji Affect API (taichusjs.cn).
Clients that support streamable-http MCP can connect directly, no local package needed:
Requires Python 3.10+.
Get an API key:
https://taichusjs.cn/trial.html.Environment variables:
generate_avatar_params requires a key tier that includes L2.empathy_hint and somatic_decode are billed as L1-family calls (trial tier applies).来源：README.md，提交 d024a60
L1 Affect Extraction: analyze text into an 8-dimensional emotion vector, emotion texture labels, causal intent classification, and a natural-language state description. text: input up to 2000 chars. lang: optional 'zh' or 'en'.
langtext必填L2 Avatar Driving Pipeline: one call returns blendshape/AU/curve animation parameters, lighting & material atmosphere package, adapter payload, plus the upstream L1 affect analysis. Requires a key tier that includes L2.
text必填L3 Empathy Response Strategy: converts text into a deterministic response strategy (approach, tone temperature, pacing, focus points, avoid-list) for AI companions and conversational agents. Deterministic table lookup, no LLM, ~20ms; privacy-first. Not a medical or therapeutic tool.
text必填L4 Somatic Emotion Decode: converts body-sensation text (e.g. tight chest, clenched fists) into structured emotion: primary affect, valence/arousal, emotion texture, causal intent, plus somatic anchor cues. Grounded in the somatic decoding discipline; wellness simulation only, not a diagnostic tool.
text必填已满足适用检查项的 100%
该评分衡量此收录条目的完整程度，依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价，也不表示服务器安全或当前可用：可连通性是带日期的检查结果，评分也不包含安装量或用户评价。
{
"mcpServers": {
"chenji-affect": {
"type": "streamable-http",
"url": "https://taichusjs.cn/mcp",
"headers": { "x-api-key": "cj-your-key-here" }
}
}
}pip install "mcp>=1.0,<2"{
"mcpServers": {
"chenji-affect": {
"command": "python",
"args": ["/absolute/path/to/server.py"],
"env": {
"CHENJI_API_KEY": "cj-your-key-here"
}
}
}
}