Hermes — Air Quality Intelligence

UK air quality MCP: live readings, historical trends, LAQM stats, WHO checks, knowledge base.

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What it can do

    What data it sees

    Do you need an account

    No: the server works without sign-in

    UK air quality MCP: live readings, historical trends, LAQM stats, WHO checks, knowledge base.

    How to connect

    How to connect Hermes — Air Quality Intelligence to Claude

    The server address to paste into Claude settings:

    https://hermes.southlondonscientific.com/mcp

    1. Open Claude (claude.ai or the desktop app).
    2. Go to Settings → Connectors.
    3. Click Add custom connector.
    4. Paste the server address copied below into Remote MCP server URL and click Add.
    5. In a chat, click + → Connectors and switch the new connector on.

    Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

    Authorization

    After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

    How to connect Hermes — Air Quality Intelligence to ChatGPT

    The server address to paste into ChatGPT settings:

    https://hermes.southlondonscientific.com/mcp

    1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
    2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
    3. Open Settings → Connectors and click Create.
    4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
    5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
    6. In a new chat open + → Apps/Connectors and enable the connector.

    OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

    Authorization

    On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

    How to connect Hermes — Air Quality Intelligence to Cursor

    The server address to paste into Cursor settings:

    https://hermes.southlondonscientific.com/mcp

    Fastest: click Open in Cursor below and confirm the prompt.

    Manually:

    1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
    2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
    3. Save the file. The server appears in the MCP list; authorize it there if asked.

    Authorization

    If the service needs sign-in, an authorize button appears next to the server in the MCP list.

    Server tool list (15)

    Raw names from tools/list. Only developers need these.

    assess_location_aqComprehensive air quality assessment for a location in one call. Combines nearby monitor discovery and current readings with DAQI into a single response. Use this as the first tool call for any air quality question about a location. For long-term trend analysis, use the dedicated `trend_analysis` tool. Returns a structured 'summary' dict with purpose-appropriate sections. Present the summary description to users first. Args: location: Postcode, place name, or "lat,lon". purpose: What the user needs — "general" (default), "health" (safety/worry), "exercise" (outdoor activity), or "planning" (homebuying/school assessment/long-term).
    get_current_aqGet the most recent air quality readings near a location, with health context. Returns a 'summary' with a plain-English health assessment and advice for general and at-risk populations. Present the summary to users first. Also returns individual 'readings' from nearby monitors and 'metadata' about data freshness and sources. Args: location: Postcode, place name, or "lat,lon". radius_km: Search radius in kilometres (default 2.0). pollutants: Optional filter, e.g. ["NO2", "PM2.5"]. sources: Optional filter, e.g. ["AURN", "BREATHE_LONDON"].
    get_historical_aqGet historical air quality data for a site or location, with health context. Returns a 'narrative' with plain-English interpretation of trends, WHO guideline exceedances, and guideline comparisons. Present the narrative to users first. Also returns raw 'data' and 'summary' statistics. Args: start_date: Start date (ISO format, e.g. "2025-01-01"). end_date: End date (ISO format). location: Postcode, place name, or "lat,lon". Provide this or site_code. site_code: Direct site code. Provide this or location. pollutants: Optional filter, e.g. ["NO2", "PM2.5"]. frequency: "hourly", "daily", or "monthly" (default "daily").
    get_aqi_summaryGet an AQI assessment with health advice and WHO compliance check. Returns a 'summary' with a plain-English health assessment, advice for general and at-risk populations, and WHO guideline context. Present the summary to users first. Also returns raw 'aqi' and 'who_compliance' data. Args: location: Postcode, place name, or "lat,lon". index: AQI system — "UK_DAQI" (default), "WHO", or "US_EPA". period: "current", "today", "this_week", or "this_month".
    list_monitorsList air quality monitoring sites near a location, with context. Returns a 'summary' explaining how many monitors were found, their operational status, and what each monitor type represents. Present the summary to users first. Also returns a 'monitors' list with full metadata. Args: location: Postcode, place name, or "lat,lon". radius_km: Search radius in kilometres (default 5.0). sources: Optional filter, e.g. ["AURN", "BREATHE_LONDON"].
    chart_aq_trendGenerate a time series chart of air quality data. Returns a PNG chart image with a brief text summary. Use this when users ask about trends, patterns, or want to visualise air quality over time. Args: start_date: Start date (ISO format, e.g. "2025-01-01"). end_date: End date (ISO format). location: Postcode, place name, or "lat,lon". Provide this or site_code. site_code: Direct site code. Provide this or location. pollutants: Optional filter, e.g. ["NO2", "PM2.5"]. Defaults to NO2, PM2.5, PM10, O3 if not specified. frequency: "hourly", "daily", or "monthly" (default "daily"). show_who_guidelines: Show WHO guideline reference lines (default True). show_daqi_bands: Show DAQI band background shading (default True).
    trend_analysisAnalyse the long-term trend in a pollutant near a location. Uses Theil-Sen slope estimation with Mann-Kendall significance testing to determine whether air quality is improving, worsening, or stable. Robust to outliers and missing data. Returns a 'summary' with plain-English trend description and statistical details. Present the summary to users first. Args: location: Postcode, place name, or "lat,lon". pollutant: Pollutant to analyse — "NO2", "PM2.5", "PM10", "O3" (default "NO2"). years: Number of years of data to analyse (default 5, range 2–5). Requests outside this range are clamped; the response includes ``metadata.years_clamped`` and a note in ``summary`` when so.
    compare_locationsCompare current air quality across multiple locations side-by-side. Returns a ranked comparison by pollutant with DAQI bands and distance to nearest monitor. Useful for comparing development sites, school locations, or residential options. Args: locations: List of 2–6 locations (postcodes, place names, or "lat,lon"). pollutants: Optional filter, e.g. ["NO2", "PM2.5"]. Default: all available.
    regulatory_statsGet LAQM Annual Status Report-style statistics for a location. Returns annual means, percentiles, exceedance counts, data capture percentages, and compliance assessment against UK legal limits and WHO guidelines. Args: location: Postcode, place name, or "lat,lon". year: Calendar year to report on (default: most recent complete year). pollutants: Optional filter, e.g. ["NO2", "PM2.5"]. Default: all available.
    time_patternsAnalyse when pollution is highest — hour of day, day of week, and month. Returns temporal profiles showing typical patterns. Useful for advising on best times for outdoor exercise, school runs, or commuting. Args: location: Postcode, place name, or "lat,lon". pollutant: Pollutant to analyse — "NO2", "PM2.5", "PM10", "O3" (default "NO2"). period: Time window — "last_month", "last_3_months", "last_6_months", or "last_year" (default).
    kb_get_guidelinesGet current air quality guideline and target values. Args: framework: "WHO", "UK", "EU", or "all" (default). pollutant: Optional filter for a specific pollutant. Returns the full guidelines document (markdown).
    kb_get_health_effectsGet health evidence summaries for a pollutant and population group. Args: pollutant: "NO2", "PM2.5", "PM10", or "O3". population_group: "general", "children", "elderly", "respiratory", "cardiovascular", or "pregnant" (default "general"). Returns health effects document (markdown).
    kb_get_local_contextGet area-specific contextual information. Args: area: "southwark", "london", or a specific neighbourhood. Returns local context document (markdown).
    kb_get_practical_adviceGeneric protective-action guidance for a category of situation (NOT keyed to an individual user's context). For *personalised* advice that takes the user's specific health situation into account (asthma, pregnancy, gas cooker, tube commute, indoor sources), prefer the Clara MCP server's `contextual_advice` tool — it composes Hermes live readings with personal context to give an answer keyed to *this* user, *now*. Use this KB tool only as a fallback or when Clara is not available. Args: situation: One of "high_pollution_day", "commuting", "exercise", "school_run", "indoor_air", "planning_objection", "pregnancy", "child_asthma". Returns practical advice document (markdown).
    kb_get_monitoring_explainerGet plain-language explanations of monitoring methods and limitations. Args: topic: One of "how_monitors_work", "regulatory_vs_lowcost", "what_readings_mean", "why_numbers_differ", "representativeness", "data_quality", "what_monitors_measure". Returns monitoring explainer document (markdown).