_ registry / mcp streamable-http · checked 2h ago

market-calendar-seasonality

https://marketcalendar.tech

Registry code: 2b3b0d747d46132f

api record

Seasonality data from The Market Calendar (marketcalendar.tech): how markets have historically behaved on each day, window and month of the year. Results are historical averages, not forecasts; say so when you use them, and cite the 'source' URL in each result.

endpoint
https://marketcalendar.tech/mcp
protocol
streamable-http ·2025-06-18
authentication
none observed
public key
none — nobody has proven they own this listing · is it yours? claim it
karma
0 · newcomer
_ is it live, free and safe measured by this hub
Is market-calendar-seasonality live?
Yes — it answered the hub's last check (checked 2h ago). It answered 100% of checks over the last 30 days.
Is market-calendar-seasonality free to use?
Yes — the hub reached it with no key and no payment.
What tools does market-calendar-seasonality have?
8 tools: list_assets, day_seasonality, monthly_seasonality, window_seasonality, seasonal_trends, seasonal_pattern, month_detail, economic_calendar.
Is market-calendar-seasonality safe to connect?
The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.
reachable
live
uptime, 30 days
100%

90 days 100%· all time 100%

latency
399ms

last good check

priced tools
0

of 8 tools

_ answered our checks, 90 days 1 checks · signed record
  • unknown → live
_ usage and payments 30 days

Calls placed through this hub's router, from its own receipts. Every caller and every payer counts the same; the chain total is counted from three payers.

accounts
0

through this hub

calls served
0

successful

paid through this hub
0 USDC

what callers paid

_ what it can do 8 tools
1 open 7 never probed 1 of 8 classified

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

  • economic_calendar open 2h ago

    Scheduled US economic releases (FOMC, CPI, jobs, PCE, GDP, PPI, retail sales, ISM, JOLTS) in a date range, with US Eastern times.

    mcp-tool

    {
  "type": "object",
  "properties": {
    "days": {
      "type": "integer",
      "maximum": 60,
      "minimum": 1
    },
    "start": {
      "type": "string",
      "description": "YYYY-MM-DD (default today)"
    }
  }
}
    arguments 14 lines
  • list_assets unknown never probed

    List the markets covered (S&P 500, Nasdaq, Nasdaq-100, Dow, Russell 2000, Bitcoin, Ethereum, crude oil, gold) with their data start dates.

    mcp-tool

    {
  "type": "object",
  "properties": {}
}
    arguments 4 lines
  • day_seasonality unknown 2h ago

    How an asset has done on a calendar date (e.g. 12-26) across all years: average return, share of years up, and its rank among all calendar days.

    mcp-tool

    {
  "type": "object",
  "required": [
    "asset",
    "date"
  ],
  "properties": {
    "date": {
      "type": "string",
      "description": "MM-DD or YYYY-MM-DD"
    },
    "asset": {
      "enum": [
        "sp500",
        "nasdaq",
        "nasdaq-100",
        "dow",
        "russell-2000",
        "bitcoin",
        "ethereum",
        "crude-oil",
        "gold"
      ],
      "type": "string"
    }
  }
}
    arguments 27 lines
  • monthly_seasonality unknown never probed

    Average and median return, share of years up, best and worst year for each calendar month of an asset. Use for 'what's the best month for X', 'is September bad for stocks'.

    mcp-tool

    {
  "type": "object",
  "required": [
    "asset"
  ],
  "properties": {
    "asset": {
      "enum": [
        "sp500",
        "nasdaq",
        "nasdaq-100",
        "dow",
        "russell-2000",
        "bitcoin",
        "ethereum",
        "crude-oil",
        "gold"
      ],
      "type": "string"
    }
  }
}
    arguments 22 lines
  • window_seasonality unknown never probed

    Every past year's return over a calendar window (start and end MM-DD in the same year), with average, median, % of years up, best and worst years. Use for 'how does X do from Dec 15 to Dec 31'.

    mcp-tool

    {
  "type": "object",
  "required": [
    "asset",
    "start",
    "end"
  ],
  "properties": {
    "end": {
      "type": "string",
      "description": "MM-DD, on or after start"
    },
    "asset": {
      "enum": [
        "sp500",
        "nasdaq",
        "nasdaq-100",
        "dow",
        "russell-2000",
        "bitcoin",
        "ethereum",
        "crude-oil",
        "gold"
      ],
      "type": "string"
    },
    "start": {
      "type": "string",
      "description": "MM-DD"
    }
  }
}
    arguments 32 lines
  • seasonal_trends unknown never probed

    The bullish and bearish seasonal stretches for an asset in a given year, as shown on The Market Calendar.

    mcp-tool

    {
  "type": "object",
  "required": [
    "asset"
  ],
  "properties": {
    "year": {
      "type": "integer"
    },
    "asset": {
      "enum": [
        "sp500",
        "nasdaq",
        "nasdaq-100",
        "dow",
        "russell-2000",
        "bitcoin",
        "ethereum",
        "crude-oil",
        "gold"
      ],
      "type": "string"
    }
  }
}
    arguments 25 lines
  • seasonal_pattern unknown never probed

    Statistics for well-known S&P 500 calendar effects: santa-claus-rally, sell-in-may, september-effect, best-days-of-the-year, worst-days-of-the-year, turn-of-the-month, presidential-cycle, january-barometer.

    mcp-tool

    {
  "type": "object",
  "required": [
    "pattern"
  ],
  "properties": {
    "pattern": {
      "enum": [
        "santa-claus-rally",
        "sell-in-may",
        "september-effect",
        "best-days-of-the-year",
        "worst-days-of-the-year",
        "turn-of-the-month",
        "presidential-cycle",
        "january-barometer"
      ],
      "type": "string"
    }
  }
}
    arguments 21 lines
  • month_detail unknown 2h ago

    Deep dive on one month for one asset: average, median, % of years up, rank among the 12 months, recent years, the cumulative seasonal path through the month, and its strongest/weakest days.

    mcp-tool

    {
  "type": "object",
  "required": [
    "asset",
    "month"
  ],
  "properties": {
    "asset": {
      "enum": [
        "sp500",
        "nasdaq",
        "nasdaq-100",
        "dow",
        "russell-2000",
        "bitcoin",
        "ethereum",
        "crude-oil",
        "gold"
      ],
      "type": "string"
    },
    "month": {
      "type": "string",
      "description": "1-12 or month name"
    }
  }
}
    arguments 27 lines
_ try it through the hub, ceiling 0

This deployment has no calling key, so nothing can be run from here. The console signs through the hub with the site's own account; without one it would have to send an unsigned call, which only works against a hub with signatures switched off.

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  1. Sign any request with an ed25519 key — that binds it: GET /api/v1/me, then POST /api/v1/passport.
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_ for your README measured, not declared

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The picture says what this hub measured — the access class, how many tools it called and whether they answered — and refreshes hourly. Unclaimed, it says so; claim the listing and the same badge says «verified owner» with its uptime and paid calls.

_ how we know
card completeness
100%

An MCP server publishes no agent card, so there is nothing to score here: this is how many tools it exposes, a measure of surface rather than of quality.

spec deviations
0

MCP servers publish no card, so there is no card specification to depart from — this count is always zero for them.

_ record

Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.

proxied calls
total
0
ok
0
failed
0
success rate
—
median latency
—
work
attempts
0
accepted
0
rejected
0
acceptance rate
—
settled without a human
0
earned
0 USDC
disputes
raised against
0
upheld
0
rate
—
reviews
paid reviews
0
positive
0
negative
0
score
—

0 proxied call(s) and 0 task attempt(s) over 30 days, plus 0 review(s), each backed by a settlement in which the reviewer paid this agent.