Stellarhound — stargazing forecasts, dark-sky sites & aurora

Live stargazing forecasts: per-night sky scores, dark-sky sites, aurora & light pollution anywhere.

CommunityOnlineNo sign-inGlobalFreeRead-only

What it can do

    What data it sees

    Do you need an account

    No: the server works without sign-in

    Live stargazing forecasts: per-night sky scores, dark-sky sites, aurora & light pollution anywhere.

    How to connect

    How to connect Stellarhound — stargazing forecasts, dark-sky sites & aurora to Claude

    The server address to paste into Claude settings:

    https://stellarhound.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 Stellarhound — stargazing forecasts, dark-sky sites & aurora to ChatGPT

    The server address to paste into ChatGPT settings:

    https://stellarhound.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 Stellarhound — stargazing forecasts, dark-sky sites & aurora to Cursor

    The server address to paste into Cursor settings:

    https://stellarhound.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 (5)

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

    get_stargazing_conditionsScore the next nights for stargazing at a location (0-100 per night). Use for "when should I stargaze this week near X", "is Saturday any good for the Milky Way", trip planning. Each night combines the three-layer cloud-cover forecast, moon illumination and up-fraction, and the astronomical-darkness window; `best_window` names the best upcoming night. Also returns the location's light-pollution estimate (approximate Bortle class + what's visible at that darkness). Args: lat: Latitude in decimal degrees (-90..90). You know city coordinates — pass them. lon: Longitude in decimal degrees (-180..180). nights: How many nights ahead to score, 1-16 (default 7; forecasts beyond ~7 nights are increasingly uncertain). Returns {timezone, light_pollution, nights:[{date, darkness, moon, cloud, score:{value, band, summary}}], best_window, uncertainty_note, attribution}. Present scores/verdicts verbatim; skies beyond ~7 days are provisional.
    get_tonight_agendaGet tonight's stargazing plan for a location: score, darkness window, and what to observe. Use when the user asks "what can I see tonight" / "is tonight worth going out". Returns tonight's sky score and darkness window plus a ranked agenda of observing targets appropriate for the location's sky darkness. Args: lat: Latitude in decimal degrees (-90..90). lon: Longitude in decimal degrees (-180..180). Returns {timezone, light_pollution, tonight:{date, darkness, weather,...}, targets/agenda entries, attribution}. Report as returned.
    find_dark_sky_sitesRecommend dark-sky sites near a location, ranked by whether the drive is worth it. Use for "where should I drive to stargaze near X". Sites are grouped by drivability (how far), then ranked by a drive-worth score combining the best weather window over the next 7 nights, how much darker the site is than the user's location, and drive time. Drive times are approximate (straight-line x 1.3), not routed. Args: lat: Latitude in decimal degrees (-90..90). lon: Longitude in decimal degrees (-180..180). limit: Max sites to return, 1-12 (default 5). Returns {ranking (methodology note), tiers:[{tier, label, hint, sites:[...]}], nearest_km, uncertainty_note, attribution} — sites grouped into drivability tiers. Include the methodology note when presenting — it explains the ordering honestly.
    get_aurora_forecastGet the aurora (northern/southern lights) outlook for a location. Use for "any chance of aurora tonight near X". Combines the Kp-index forecast with the location's geomagnetic latitude to say whether aurora could be visible there, and when. Args: lat: Latitude in decimal degrees (-90..90). lon: Longitude in decimal degrees (-180..180). Returns {kp_forecast:[{time, kp, flag: observed|estimated|predicted}, ...], visibility assessment fields, attribution}. Kp entries are flagged by how firm they are — keep those labels when presenting.
    get_light_pollutionEstimate light pollution at any point: approximate Bortle class and what's visible there. Use for "how dark is the sky at X" / "can I see the Milky Way from X". Returns the zenith-brightness-derived estimate (mpsas, approximate Bortle class) and a plain-language ceiling: what the Milky Way, naked-eye and telescope views are like under that sky. This is a satellite-data estimate, not a field measurement — say so. Args: lat: Latitude in decimal degrees (-90..90). lon: Longitude in decimal degrees (-180..180). Returns {light_pollution:{bortle_approx, mpsas, ceiling:{label, milky_way, naked_eye, telescope}, note}, attribution}.