B.O.N.S.A.I. Health Intelligence API

Lifestyle medicine health intelligence via x402 micropayments. 637+ peer-reviewed references.

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Qualität und Sicherheit

B
Qualität der Beschreibung
78%
Vollständigkeit des Schemas
81%
Qualität der Benennung
87%
Risiko der Vergiftung
100%
Übereinstimmung der Berechtigungen
100%
Einhaltung des Protokolls
100%

Befunde (4)

  • LOWTool 'query_nutrition_topic' description lacks action verbin query_nutrition_topic
  • LOWTool 'interpret_labs' description lacks action verbin interpret_labs
  • LOWTool 'drug_safety' description lacks action verbin drug_safety
  • LOWTool 'lifestyle_query' description lacks action verbin lifestyle_query

Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.

Kontextkosten

~1,366Tokens (Tool-Definitionen)
~882 BTypische Antwortgröße
Mittlere Auswirkung auf die Aufmerksamkeit (1.07% von 128k Kontext)

Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.

Installieren

Installation mit einem Klick

Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:

{
  "mcpServers": {
    "bonsai-health": {
      "url": "https://web-production-ae61.up.railway.app"
    }
  }
}

Remote-Endpunkte

https://web-production-ae61.up.railway.appstreamable-http

Was es kann

Tool-Inventar

Tools (9)

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🟢get_protocol(condition, user_context, duration_weeks)

Generate an evidence-based whole-food plant-based protocol for one of 47 chronic conditions. Returns therapeutic foods, daily meal structure, foods to minimize, monitoring markers, and clinical citations.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "condition": {
      "type": "string",
      "enum": [
        "angina",
        "anxiety",
        "ascvd",
        "asthma",
        "atrial_fibrillation",
        "autoimmune",
        "barretts",
        "bipolar_disorder",
        "chronic_kidney_disease",
        "chronic_pain",
        "copd",
        "depression",
        "diabetes",
        "diabetes_kidney_protection",
        "diabetes_with_lipid_risk",
        "dvt_pe_history",
        "edema",
        "epilepsy",
        "exercise_induced_bronchospasm",
        "fibromyalgia",
        "gerd",
        "gi_health",
        "gout",
        "h_pylori",
        "heart_failure",
        "hypercoagulable",
        "hyperlipidemia",
        "hypertension",
        "hyperthyroidism",
        "hyperuricemia",
        "hypothyroidism",
        "ibd",
        "lupus",
        "mechanical_valve",
        "obesity",
        "ocd_ptsd",
        "other_autoimmune",
        "pcos",
        "peptic_ulcer",
        "post_thyroidectomy",
        "prediabetes",
        "psoriasis",
        "rheumatoid_arthritis",
        "severe_acne",
        "stroke_history",
        "type_2_diabetes",
        "weight_management"
      ]
    },
    "user_context": {
      "type": "object"
    },
    "duration_weeks": {
      "type": "integer",
      "default": 4,
      "minimum": 1,
      "maximum": 24
    }
  },
  "required": [
    "condition"
  ]
}
🟢query_nutrition_topic(query, max_results)

Ask a nutrition or food-as-medicine question. Returns evidence-based answer from the 200-chunk lifestyle medicine knowledge base.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string"
    },
    "max_results": {
      "type": "integer",
      "default": 3,
      "minimum": 1,
      "maximum": 10
    }
  },
  "required": [
    "query"
  ]
}
🟢interpret_labs(lab_values, current_medications, health_goals)

Interpret a panel of lab values against ACLM-optimized reference ranges. Returns risk classification per marker, lifestyle interventions, and medication deprescription signals.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "lab_values": {
      "type": "object",
      "description": "Key-value pairs of biomarker names and values. Common keys: hba1c, fasting_glucose, fasting_insulin, ldl, hdl, triglycerides, apob, lp_a, hscrp, vitamin_d, b12, ferritin, tsh, free_t4, free_t3."
    },
    "current_medications": {
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "health_goals": {
      "type": "array",
      "items": {
        "type": "string"
      }
    }
  },
  "required": [
    "lab_values"
  ]
}
🟢marker_reference(marker)

Look up the ACLM-optimized reference range and lifestyle intervention plan for a single biomarker (e.g., apob, lp_a, hscrp, hba1c, fasting_insulin, vitamin_d).

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "marker": {
      "type": "string"
    }
  },
  "required": [
    "marker"
  ]
}
🟢glp_protocol(glp1_phase, glp1_medication, condition, user_context)

Generate a GLP-aware nutrition protocol composed on top of any active chronic condition. Returns protein floor (1.2-1.6 g/kg), fiber ramp schedule, GI tolerance interventions, resistance training prescription, hydration target, and phase-specific guidance.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "glp1_phase": {
      "type": "string",
      "enum": [
        "starting",
        "titrating",
        "maintenance",
        "tapering",
        "post_drug"
      ]
    },
    "glp1_medication": {
      "type": "string",
      "enum": [
        "semaglutide",
        "tirzepatide",
        "liraglutide",
        "dulaglutide",
        "compounded",
        "saxenda"
      ]
    },
    "condition": {
      "type": "string"
    },
    "user_context": {
      "type": "object"
    }
  },
  "required": [
    "glp1_phase",
    "glp1_medication"
  ]
}
🟢glp_phase_guide(glp1_phase)

Return the protocol overview for a specific GLP-1 therapy phase (starting, titrating, maintenance, tapering, post_drug).

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "glp1_phase": {
      "type": "string",
      "enum": [
        "starting",
        "titrating",
        "maintenance",
        "tapering",
        "post_drug"
      ]
    }
  },
  "required": [
    "glp1_phase"
  ]
}
🟢check_interactions(medications, foods_or_supplements)

Check a list of medications for food-drug interactions, nutrient depletions, and timing-critical dosing requirements.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "medications": {
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "foods_or_supplements": {
      "type": "array",
      "items": {
        "type": "string"
      }
    }
  },
  "required": [
    "medications"
  ]
}
🟢drug_safety(medication)

Return the food-drug safety profile for a single medication.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "medication": {
      "type": "string"
    }
  },
  "required": [
    "medication"
  ]
}
🟢lifestyle_query(query, pillar, max_results)

Ask any lifestyle medicine question. Returns evidence-based answer with citations from a 200-chunk knowledge base spanning ACLM 6-pillars, B.O.N.S.A.I. nutrition, drug-food interactions, lab interpretation, GLP guidance, wearables, and CGM signal interpretation.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string"
    },
    "pillar": {
      "type": "string",
      "enum": [
        "nutrition",
        "movement",
        "sleep",
        "stress",
        "substance_use",
        "social_connection",
        "labs",
        "wearables",
        "any"
      ],
      "default": "any"
    },
    "max_results": {
      "type": "integer",
      "default": 3,
      "minimum": 1,
      "maximum": 10
    }
  },
  "required": [
    "query"
  ]
}

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