io.github.zhiyu-devPublished by GitHub account zhiyu-devv1.1.0Updated Oct 24, 2026
Affect analysis, 3D avatar params, empathy hints and somatic emotion decode.
Chenji Affect is a remote MCP server that turns text into structured affect signals: emotion vectors, avatar animation parameters, empathy strategies and body-s
Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.
Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.
Read https://sourceweft.com/mcp/io.github.zhiyu-dev%2Fchenji-affect-mcp/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.Add this to your client's mcpServers config.
{
"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).Source: README.md at commit 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'.
langtextrequiredL2 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.
textrequiredL3 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.
textrequiredL4 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.
textrequired100% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
{
"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"
}
}
}
}