market-data

Verified market data for AI trading agents: quality-flagged candles, funding, OI, order flow. x402.

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Qualität und Sicherheit

A
Qualität der Beschreibung
89%
Vollständigkeit des Schemas
71%
Qualität der Benennung
97%
Risiko der Vergiftung
100%
Übereinstimmung der Berechtigungen
100%
Einhaltung des Protokolls
100%

Befunde (6)

  • LOWTool 'describe_catalog' description lacks action verbin describe_catalog
  • LOWTool 'get_bars' description lacks action verbin get_bars
  • LOWTool 'get_regime_label' description lacks action verbin get_regime_label
  • LOWTool 'get_context' description lacks action verbin get_context
  • LOWTool 'get_events' description lacks action verbin get_events
  • LOWTool 'get_insider' description lacks action verbin get_insider

Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.

Kontextkosten

~1,964Tokens (Tool-Definitionen)
~448 BTypische Antwortgröße
Mittlere Auswirkung auf die Aufmerksamkeit (1.53% von 128k Kontext)

Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.

Installieren

Installation mit einem Klick

Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:

{
  "mcpServers": {
    "market-data": {
      "url": "https://iturri.ai/mcp"
    }
  }
}

Remote-Endpunkte

https://iturri.ai/mcpstreamable-http

Was es kann

Tool-Inventar

Tools (22)

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🟢describe_catalog

Free discovery: symbols, timeframes, ranges, pricing, quality legend.

Eingabe-Schema

{
  "type": "object",
  "properties": {}
}
🟢get_bars(symbol, tf, start, end)

Quality-flagged OHLCV candles. Priced per 1,000 candles.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "symbol": {
      "type": "string"
    },
    "tf": {
      "type": "string"
    },
    "start": {
      "type": "string"
    },
    "end": {
      "type": "string"
    }
  },
  "required": [
    "symbol",
    "tf"
  ]
}
🟢get_features(symbol, tf, start, end)

Documented leakage-safe feature matrix rows. Priced per call.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "symbol": {
      "type": "string"
    },
    "tf": {
      "type": "string"
    },
    "start": {
      "type": "string"
    },
    "end": {
      "type": "string"
    }
  },
  "required": [
    "symbol",
    "tf"
  ]
}
⚪build_bundle(pack, symbol, tf)

Signed URL for a dataset SKU. Packs: crypto|equities ($59 each), everything ($149: both packs + all token sequences, $730 list), tokens ($18/symbol), dataset (per-symbol OHLCV, crypto $14 / equity $5), mtf (aligned multi-timeframe bundle $9, crypto only), features (feature matrix, crypto $7 / equity $4). Priced as the SKU.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "pack": {
      "type": "string",
      "enum": [
        "crypto",
        "equities",
        "tokens",
        "dataset",
        "mtf",
        "features",
        "everything"
      ]
    },
    "symbol": {
      "type": "string",
      "description": "required for tokens|dataset|mtf|features"
    },
    "tf": {
      "type": "string",
      "description": "features only — crypto: 1h (default) or 15m; equity: 1d"
    }
  },
  "required": [
    "pack"
  ]
}
🟢get_regime_label(symbol, timestamp)

Descriptive market-state label (trend/range × calm/vol quadrant) for the most recent completed bar at or before a timestamp. Not a prediction.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "symbol": {
      "type": "string"
    },
    "timestamp": {
      "type": "string"
    }
  },
  "required": [
    "symbol",
    "timestamp"
  ]
}
🟢get_funding(symbol, start, end)

Perp funding-rate settlement history from listing date (checksummed archive).

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "symbol": {
      "type": "string"
    },
    "start": {
      "type": "string"
    },
    "end": {
      "type": "string"
    }
  },
  "required": [
    "symbol"
  ]
}
🟢get_open_interest(symbol, tf, start, end)

Open interest with per-row quality flags (verified archive + flagged bridge). tf=1h (default, full history) or tf=5m (archive-native 5-minute rows from 2020-09; ranged pulls, ~100k rows max per call).

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "symbol": {
      "type": "string"
    },
    "tf": {
      "type": "string",
      "enum": [
        "1h",
        "5m"
      ]
    },
    "start": {
      "type": "string"
    },
    "end": {
      "type": "string"
    }
  },
  "required": [
    "symbol"
  ]
}
🟢get_long_short(symbol, start, end)

Positioning ratios at 5-minute cadence from the checksummed venue archive (2020-09+): top-trader long/short by accounts and by position size, all-accounts long/short, taker buy/sell volume ratio. Ranged pulls, ~100k rows max per call.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "symbol": {
      "type": "string"
    },
    "start": {
      "type": "string"
    },
    "end": {
      "type": "string"
    }
  },
  "required": [
    "symbol"
  ]
}
🟢get_context(series, start, end)

Context series: fear_greed_1d, VIX_1d, DXY_1d, TNX_1d, DJI_1d.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "series": {
      "type": "string"
    },
    "start": {
      "type": "string"
    },
    "end": {
      "type": "string"
    }
  },
  "required": [
    "series"
  ]
}
🟢get_events(type, start, end)

Curated macro/crypto events (FOMC w/ surprise, halvings, incidents) in a range.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "type": {
      "type": "string"
    },
    "start": {
      "type": "string"
    },
    "end": {
      "type": "string"
    }
  }
}
🟢get_orderflow(symbol, tf, start, end)

Taker buy/sell imbalance, trade counts, quote volume (1h/1d via API; denser tiers in packs). buy_ratio 0.5 = balanced.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "symbol": {
      "type": "string"
    },
    "tf": {
      "type": "string",
      "enum": [
        "1h",
        "1d"
      ]
    },
    "start": {
      "type": "string"
    },
    "end": {
      "type": "string"
    }
  },
  "required": [
    "symbol"
  ]
}
⚪validate_backtest_data(symbol, tf, start, end)

Quality report for a dataset spec before you backtest on it: coverage, per-bar quality distribution, gaps, and concrete warnings.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "symbol": {
      "type": "string"
    },
    "tf": {
      "type": "string"
    },
    "start": {
      "type": "string"
    },
    "end": {
      "type": "string"
    }
  },
  "required": [
    "symbol",
    "tf"
  ]
}
🟡audit_my_data(symbol, tf, bars)

FREE: submit YOUR OHLCV bars and get an accuracy verdict against the verified archive — score, worst windows, systematic-offset findings. Tells you what's wrong, not the corrected values (that's get_bars).

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "symbol": {
      "type": "string"
    },
    "tf": {
      "type": "string"
    },
    "bars": {
      "type": "object",
      "description": "columnar arrays: t (epoch s or ISO) required; o/h/l/c optional",
      "properties": {
        "t": {
          "type": "array"
        },
        "o": {
          "type": "array"
        },
        "h": {
          "type": "array"
        },
        "l": {
          "type": "array"
        },
        "c": {
          "type": "array"
        }
      }
    }
  },
  "required": [
    "symbol",
    "tf",
    "bars"
  ]
}
🟡lookahead_check(symbol, tf, signals)

FREE: submit backtest signals ({t, price}) and get an execution-feasibility verdict — impossible fills outside the bar's traded range, fills pinned at bar extremes (classic lookahead bias).

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "symbol": {
      "type": "string"
    },
    "tf": {
      "type": "string"
    },
    "signals": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "t": {},
          "price": {
            "type": "number"
          },
          "side": {
            "type": "string"
          }
        }
      }
    }
  },
  "required": [
    "symbol",
    "tf",
    "signals"
  ]
}
🟡survivorship_check(symbols, start, end, asset)

FREE: submit a backtest universe + window and get a survivorship-bias verdict — which of your symbols died mid-window, and which delisted symbols we cover that your universe omits.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "symbols": {
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "start": {
      "type": "string"
    },
    "end": {
      "type": "string"
    },
    "asset": {
      "type": "string",
      "enum": [
        "crypto",
        "equity"
      ]
    }
  },
  "required": [
    "symbols"
  ]
}
🟢get_fundamentals(symbol, concept, start, end, as_of)

Point-in-time SEC XBRL fundamentals (80 filers, incl. delisted): every restatement vintage with its filed date. Pass as_of for what was knowable then. Filter by concept (e.g. Assets, Revenues).

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "symbol": {
      "type": "string"
    },
    "concept": {
      "type": "string"
    },
    "start": {
      "type": "string"
    },
    "end": {
      "type": "string"
    },
    "as_of": {
      "type": "string"
    }
  },
  "required": [
    "symbol"
  ]
}
🟡get_insider(symbol, start, end)

SEC Form 4 insider transactions as filed (80 symbols, since 2016): officer/director trades with shares, price, post-trade holdings.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "symbol": {
      "type": "string"
    },
    "start": {
      "type": "string"
    },
    "end": {
      "type": "string"
    }
  },
  "required": [
    "symbol"
  ]
}
🟢get_institutional(symbol, start, end)

Quarterly 13F institutional aggregates (81 symbols): holders, shares, value + QoQ deltas from SEC DERA structured tables.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "symbol": {
      "type": "string"
    },
    "start": {
      "type": "string"
    },
    "end": {
      "type": "string"
    }
  },
  "required": [
    "symbol"
  ]
}
🟢get_funding_spread(symbol, start, end)

Hourly CEX-vs-DEX funding spread (67 symbols): Hyperliquid funding vs Binance 1h-equivalent, from HL genesis 2023-05.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "symbol": {
      "type": "string"
    },
    "start": {
      "type": "string"
    },
    "end": {
      "type": "string"
    }
  },
  "required": [
    "symbol"
  ]
}
🟢get_market_pulse

FREE daily pulse across the catalog: regime flips, funding extremes, CEX-vs-DEX spread extremes, biggest daily moves. One day of values — the history behind each number is the priced product.

Eingabe-Schema

{
  "type": "object",
  "properties": {}
}
🟢get_whats_new

FREE: what the daily refresh changed — dataset windows extended vs ~7 days ago, new symbols and sections, freshness per asset class.

Eingabe-Schema

{
  "type": "object",
  "properties": {}
}
🟢get_quality_receipts

FREE public scoreboard: last 30 daily fresh-data audits (cross-venue in-band vs Coinbase, 1m->1h rebuild exactness, depth sanity) — failures included, not hidden.

Eingabe-Schema

{
  "type": "object",
  "properties": {}
}

Empfohlene Prompts

retrieve_data
Get details about [item] from market-data
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fetch_info
Fetch [information type] using market-data
Erwartete Tools: get_bars

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