mcpbeat

Hermes — Air Quality Intelligence MCP Server

com.southlondonscientific/hermes
answering

Hermes — Air Quality Intelligence is answering right now. Last checked 14 min ago. It exposes 15 tools.

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

Uptime history 41 hours of history
41 hours agonow
100.0%
Uptime 24h
91 of 91 checks
15
Tools
read from the server
51 ms
Response time
average over 24h
open, no key
Access
streamable-http

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 14 min ago.

run in your terminal
claude mcp add hermes --transport http https://hermes.southlondonscientific.com/mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "hermes": {
      "url": "https://hermes.southlondonscientific.com/mcp"
    }
  }
}
~/.codex/config.toml
[mcp_servers.hermes]
url = "https://hermes.southlondonscientific.com/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "hermes": {
      "url": "https://hermes.southlondonscientific.com/mcp"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "hermes": {
      "url": "https://hermes.southlondonscientific.com/mcp"
    }
  }
}

Available tools 15

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

aqi
get_aqi_summary
Get 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".
assess
assess_location_aq
Comprehensive 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).
chart
chart_aq_trend
Generate 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).
compare
compare_locations
Compare 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.
current
get_current_aq
Get 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"].
guidelines
kb_get_guidelines
Get 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).
health
kb_get_health_effects
Get 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).
historical
get_historical_aq
Get 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").
local
kb_get_local_context
Get area-specific contextual information. Args: area: "southwark", "london", or a specific neighbourhood. Returns local context document (markdown).
monitoring
kb_get_monitoring_explainer
Get 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).
monitors
list_monitors
List 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"].
practical
kb_get_practical_advice
Generic 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).
regulatory
regulatory_stats
Get 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
time_patterns
Analyse 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).
trend
trend_analysis
Analyse 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.

Endpoints

URLTransportStateLatencyChecked
https://hermes.southlondonscientific.com/mcp streamable-http answering 48 ms 14 min ago

Hermes — Air Quality Intelligence — questions

Answers built from our own checks of this server.

What can Hermes — Air Quality Intelligence do?
It exposes 15 tools, read directly from the server on our last check. Among them: assess_location_aq, chart_aq_trend, compare_locations, get_aqi_summary, get_current_aq, get_historical_aq and 9 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
Is Hermes — Air Quality Intelligence working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 51 ms. The bar chart above shows every period we have measured.
How do I connect Hermes — Air Quality Intelligence?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does Hermes — Air Quality Intelligence need an API key?
No. Hermes — Air Quality Intelligence completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 15 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is Hermes — Air Quality Intelligence?
It answers our handshake in 51 ms on average, which is faster than 97% of all working MCP servers we measure. That puts it in the quick quarter of the ecosystem. The comparison comes from our own checks across the whole registry, every 15 minutes.