Clara — Personal Clean Air Planner

UK personal air quality advice and daily exposure assessment. Pairs with Hermes for live data.

사용해야 할까요

품질 및 안전성

A
설명 품질
100%
스키마 완전성
65%
이름 품질
80%
오염 위험
100%
권한 일치
100%
프로토콜 준수
100%

도구 정의와 프로토콜 준수에 대한 자동 분석을 기반으로 합니다.

컨텍스트 비용

~1,036토큰 (도구 정의)
~2.4 KB일반적인 응답 크기
중간 정도의 주의 영향 (128k 컨텍스트의 0.81%)

이는 서버의 도구가 모델의 컨텍스트에 로드될 때마다 소비되는 대략적인 토큰 수입니다. 수치가 높을수록 다른 작업에 사용할 수 있는 주의가 줄어듭니다.

설치

원클릭 설치

`claude_desktop_config.json` 파일에 다음을 추가하세요:

{
  "mcpServers": {
    "clara": {
      "url": "https://clara-mcp.southlondonscientific.com/mcp"
    }
  }
}

원격 엔드포인트

https://clara-mcp.southlondonscientific.com/mcpstreamable-http

할 수 있는 일

도구 목록

도구 (2)

🟢 읽기 전용🟡 쓰기🔴 삭제⚪ 알 수 없음
🟢contextual_advice(postcode, latitude, longitude, pm25, no2, ...)

Personalised air quality advice for a UK location and a specific user context. Use this tool whenever the user asks an air-quality question that depends on *who they are* or *what they're about to do*: e.g. asthma, pregnancy, school-age child, gas cooker at home, tube commute, outdoor exercise. It composes location-specific pollution with the user's personal context to produce evidence-based advice — far more targeted than a generic "high pollution day" handout. Composable with Hermes: pass pm25/no2 from Hermes get_current_aq for advice based on live readings rather than annual average estimates. Returns structured advice with a plain-English summary, health context, and local intervention information. Present the 'summary' to users first. Args: postcode: UK postcode (e.g. "SE17 1RL"). Provides coords + LAEI pollution. latitude: Latitude for coordinate-based lookup. longitude: Longitude for coordinate-based lookup. pm25: PM2.5 concentration in ug/m3. Overrides location-based estimate. no2: NO2 concentration in ug/m3. Overrides location-based estimate. setting: Context — residential, school, workplace, outdoor_exercise, commute. has_gas_cooker: Whether the person has a gas cooker (affects indoor advice). commute_mode: If setting is commute — walk, cycle, bus, car, train, tube. has_indoor_sources: Indoor pollution sources (smoking, woodstove). audience: Target audience — general, children, elderly, respiratory, pregnant.

입력 스키마

{
  "type": "object",
  "properties": {
    "postcode": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Postcode"
    },
    "latitude": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Latitude"
    },
    "longitude": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Longitude"
    },
    "pm25": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Pm25"
    },
    "no2": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "No2"
    },
    "setting": {
      "default": "residential",
      "title": "Setting",
      "type": "string"
    },
    "has_gas_cooker": {
      "default": false,
      "title": "Has Gas Cooker",
      "type": "boolean"
    },
    "commute_mode": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Commute Mode"
    },
    "has_indoor_sources": {
      "default": false,
      "title": "Has Indoor Sources",
      "type": "boolean"
    },
    "audience": {
      "default": "general",
      "title": "Audience",
      "type": "string"
    }
  },
  "title": "contextual_adviceArguments"
}
⚪exposure_assessment(home_postcode, work_postcode, transport_mode, work_frequency, commute_hour, ...)

Estimate personal daily air pollution exposure across home, work, and commute. Uses time-weighted modelling across environments: home (with indoor source adjustments), work, and commute (with route-based pollution and transport mode factors). Based on annual average pollution estimates, not live readings. Args: home_postcode: Home location UK postcode (e.g. "SE17 1RL"). Required. work_postcode: Work/school location postcode. Omit if not commuting. transport_mode: Commute mode — walk, cycle, bus, car, train, tube. work_frequency: How often you commute — most_days, some_days, less_often, never. commute_hour: Hour of commute (0-23) for time-of-day pollution adjustment. cooker_type: Home cooker type — gas, electric, induction, unknown. smoking_at_home: Whether anyone smokes indoors (major PM2.5 source). tube_line: London Underground line for tube commuters (e.g. "victoria").

입력 스키마

{
  "type": "object",
  "properties": {
    "home_postcode": {
      "title": "Home Postcode",
      "type": "string"
    },
    "work_postcode": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Work Postcode"
    },
    "transport_mode": {
      "default": "walk",
      "title": "Transport Mode",
      "type": "string"
    },
    "work_frequency": {
      "default": "most_days",
      "title": "Work Frequency",
      "type": "string"
    },
    "commute_hour": {
      "anyOf": [
        {
          "type": "integer"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Commute Hour"
    },
    "cooker_type": {
      "default": "unknown",
      "title": "Cooker Type",
      "type": "string"
    },
    "smoking_at_home": {
      "default": false,
      "title": "Smoking At Home",
      "type": "boolean"
    },
    "tube_line": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "title": "Tube Line"
    }
  },
  "required": [
    "home_postcode"
  ],
  "title": "exposure_assessmentArguments"
}

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