Chenji Affect
Affect analysis, 3D avatar params, empathy hints and somatic emotion decode.
Installation
Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).
claude mcp add --transport http chenji-affect 'https://taichusjs.cn/mcp' --header 'x-api-key: <Chenji API key (free BASIC tier on RapidAPI or taichusjs.cn)>'{
"mcpServers": {
"chenji-affect": {
"type": "http",
"url": "https://taichusjs.cn/mcp",
"headers": {
"x-api-key": "<Chenji API key (free BASIC tier on RapidAPI or taichusjs.cn)>"
}
}
}
}Documentation
Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.
Sommaire
Chenji Affect MCP Server
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).
Tools
| Tool | Level | Description |
|---|---|---|
analyze_text | L1 | Text → 8-dim affect vector + emotion texture + intent + state description |
generate_avatar_params | L2 | Text → blendshape/AU/curve animation package + lighting/atmosphere package + upstream L1 |
empathy_hint | L3 | Text → deterministic empathy response strategy (approach, tone, pacing, focus, avoid-list), ~20ms, no LLM |
somatic_decode | L4 | Body-sensation text → structured emotion (primary affect, valence/arousal, texture, intent) + somatic anchors |
Remote mode (no install)
Clients that support streamable-http MCP can connect directly, no local package needed:
{
"mcpServers": {
"chenji-affect": {
"type": "streamable-http",
"url": "https://taichusjs.cn/mcp",
"headers": { "x-api-key": "cj-your-key-here" }
}
}
}Install
Requires Python 3.10+.
pip install "mcp>=1.0,<2"Get an API key:
- Free BASIC plan (100 req/day, 3,000/month): subscribe on RapidAPI, or request a trial key at
https://taichusjs.cn/trial.html.
Configure (Claude Desktop example)
{
"mcpServers": {
"chenji-affect": {
"command": "python",
"args": ["/absolute/path/to/server.py"],
"env": {
"CHENJI_API_KEY": "cj-your-key-here"
}
}
}
}Environment variables:
| Variable | Required | Description |
|---|---|---|
CHENJI_API_KEY | Yes | Your Chenji API key |
CHENJI_API_BASE | No | Defaults to https://taichusjs.cn |
Notes
- L1 input is limited to 2000 characters (every 200 chars = 1 billing unit).
generate_avatar_paramsrequires a key tier that includes L2.empathy_hintandsomatic_decodeare billed as L1-family calls (trial tier applies).- Privacy: raw text is never persisted by the API; only key hashes and telemetry are retained.
- Wellness and affect-state simulation only — not a medical or diagnostic tool.
Links
- Website: https://taichusjs.cn
- RapidAPI listing: https://rapidapi.com/zhiyudev/api/chenji-affect-api
- Machine-readable capability card: https://taichusjs.cn/.well-known/capability.jsonld
Questions fréquentes
Qu'est-ce que Chenji Affect ?
Affect analysis, 3D avatar params, empathy hints and somatic emotion decode.
Comment installer Chenji Affect ?
Il fonctionne comme serveur distant. Dans Claude Code : claude mcp add --transport http chenji-affect 'https://taichusjs.cn/mcp' --header 'x-api-key: <Chenji API key (free BASIC tier on RapidAPI or taichusjs.cn)>'. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.
Faut-il une clé API pour Chenji Affect ?
Oui. Il attend x-api-key, à renseigner dans sa configuration.
Chenji Affect est-il open source ?
Oui. Son code est sur GitHub sous licence MIT.
Qui maintient Chenji Affect ?
Il est publié par zhiyu-dev. AI.tn le référence sans le maintenir ni le recommander.
Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.