Server definition

Hash: sha256:1291514ba972845fcc71fc6b7b7edbda90e862f56b1a2546d6c26204a2a878f5
What it is: What a remote MCP server returned when asked what it offers: 4 tools

The blob, as servednamed by its sha256

{
  "instructions": "Chenji Affect tools convert natural-language text into structured affect signals: an 8-dimensional emotion vector, emotion texture labels, causal intent, optional 3D avatar driving parameters, plus empathy response strategies and somatic-sensation-to-emotion decoding. Calls are billed by the Chenji API key supplied via the x-api-key header.",
  "tools": [
    {
      "description": "L1 Affect Extraction: analyze text into an 8-dimensional emotion vector,\n    emotion texture labels, causal intent classification, and a natural-language\n    state description. text: input up to 2000 chars. lang: optional 'zh' or 'en'.",
      "inputSchema": {
        "properties": {
          "lang": {
            "default": "",
            "title": "Lang",
            "type": "string"
          },
          "text": {
            "title": "Text",
            "type": "string"
          }
        },
        "required": [
          "text"
        ],
        "title": "analyze_textArguments",
        "type": "object"
      },
      "name": "analyze_text",
      "outputSchema": {
        "properties": {
          "result": {
            "title": "Result",
            "type": "string"
          }
        },
        "required": [
          "result"
        ],
        "title": "analyze_textOutput",
        "type": "object"
      }
    },
    {
      "description": "L3 Empathy Response Strategy: converts text into a deterministic response\n    strategy (approach, tone temperature, pacing, focus points, avoid-list) for\n    AI companions and conversational agents. Deterministic table lookup, no LLM,\n    ~20ms; privacy-first. Not a medical or therapeutic tool.",
      "inputSchema": {
        "properties": {
          "text": {
            "title": "Text",
            "type": "string"
          }
        },
        "required": [
          "text"
        ],
        "title": "empathy_hintArguments",
        "type": "object"
      },
      "name": "empathy_hint",
      "outputSchema": {
        "properties": {
          "result": {
            "title": "Result",
            "type": "string"
          }
        },
        "required": [
          "result"
        ],
        "title": "empathy_hintOutput",
        "type": "object"
      }
    },
    {
      "description": "L2 Avatar Driving Pipeline: one call returns blendshape/AU/curve animation\n    parameters, lighting & material atmosphere package, adapter payload, plus the\n    upstream L1 affect analysis. Requires a key tier that includes L2.",
      "inputSchema": {
        "properties": {
          "text": {
            "title": "Text",
            "type": "string"
          }
        },
        "required": [
          "text"
        ],
        "title": "generate_avatar_paramsArguments",
        "type": "object"
      },
      "name": "generate_avatar_params",
      "outputSchema": {
        "properties": {
          "result": {
            "title": "Result",
            "type": "string"
          }
        },
        "required": [
          "result"
        ],
        "title": "generate_avatar_paramsOutput",
        "type": "object"
      }
    },
    {
      "description": "L4 Somatic Emotion Decode: converts body-sensation text (e.g. tight chest,\n    clenched fists) into structured emotion: primary affect, valence/arousal,\n    emotion texture, causal intent, plus somatic anchor cues. Grounded in the\n    somatic decoding discipline; wellness simulation only, not a diagnostic tool.",
      "inputSchema": {
        "properties": {
          "text": {
            "title": "Text",
            "type": "string"
          }
        },
        "required": [
          "text"
        ],
        "title": "somatic_decodeArguments",
        "type": "object"
      },
      "name": "somatic_decode",
      "outputSchema": {
        "properties": {
          "result": {
            "title": "Result",
            "type": "string"
          }
        },
        "required": [
          "result"
        ],
        "title": "somatic_decodeOutput",
        "type": "object"
      }
    }
  ]
}

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