TickerDB

Pre-computed market data that improves agent reasoning, reduces token usage, and replaces pipelines.

Sollte ich dies verwenden

Qualität und Sicherheit

A
Qualität der Beschreibung
100%
Vollständigkeit des Schemas
76%
Qualität der Benennung
100%
Risiko der Vergiftung
100%
Übereinstimmung der Berechtigungen
100%
Einhaltung des Protokolls
100%

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

Kontextkosten

~4,809Tokens (Tool-Definitionen)
~4.1 KBTypische Antwortgröße
Erhebliche Auswirkung auf die Aufmerksamkeit (3.76% 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": {
    "mcp-server": {
      "command": "npx",
      "args": [
        "tickerdb-mcp"
      ]
    }
  }
}

Ausführbare Pakete

npmtickerdb-mcp1.8.6stdio

Remote-Endpunkte

https://mcp.tickerdb.com/mcpstreamable-http

Was es kann

Tool-Inventar

Tools (9)

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🟢get_summary(ticker, timeframe, date, start, end, ...)

Get pre-computed market intelligence for a specific stock, crypto, or ETF ticker. Supports 4 modes: (1) Snapshot (default) for the latest categorical state; (2) Historical snapshot by date; (3) Historical series with start and end dates; (4) Events by field and optional band, including aftermath fields on paid tiers, weekly trend_stage analysis, pattern setup states such as pattern_bull_flag and pattern_ascending_triangle, MA signal fields, trend_ma_crossover_event, MA distance lookbacks such as trend_distance_ma40, and stock-only fundamentals_free_cash_flow events. Add stats=true in event mode to return aggregate event-band and aftermath distributions instead of raw rows. Results can include freshness via as_of_date, same-candle OHLCV, market_cap, market_cap_tier, trend, momentum (including raw rsi, stochastic_k, stochastic_d alongside their zones, divergence_detected, divergence_type, stochastic_zone), volatility (including squeeze_active, squeeze_days), volume (including climax_detected, climax_type), patterns, support/resistance, levels (paid tiers), sector_context (rsi_zone, trend, agreement, asset_vs_sector_rsi), and stock-only fundamentals such as raw pe_ratio (latest ratio on or before the snapshot date; negative values preserved and unavailable values null), free_cash_flow, growth_zone, earnings_proximity, earnings_proximity_basis, analyst_consensus, valuation_percentile, and nested insider_activity when available. Raw momentum values (momentum.rsi 0-100, momentum.stochastic_k, momentum.stochastic_d) are the exact numbers behind their zones for all asset classes and both timeframes, null while lookbacks form; query zone transitions via momentum_rsi_zone / momentum_stochastic_zone, not the raw values. Summary keeps sibling _meta objects off by default; set meta=true or request explicit *_meta fields when paid-tier stability metadata is needed.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "ticker": {
      "type": "string",
      "description": "Ticker symbol, e.g. AAPL, BTCUSD, SPY"
    },
    "timeframe": {
      "type": "string",
      "enum": [
        "daily",
        "weekly"
      ],
      "description": "Analysis timeframe. Default: daily"
    },
    "date": {
      "type": "string",
      "description": "Historical date (YYYY-MM-DD) for a point-in-time snapshot. Requires Plus or Pro plan. Omit for latest."
    },
    "start": {
      "type": "string",
      "description": "Range start date (YYYY-MM-DD). Use with end for historical series."
    },
    "end": {
      "type": "string",
      "description": "Range end date (YYYY-MM-DD). Use with start for historical series."
    },
    "fields": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Optional summary fields to return. Identity fields such as market_cap and market_cap_tier are always kept. Pass sections like ohlcv, trend, momentum, volatility, volume, patterns, extremes, support_level, resistance_level, fundamentals, sector_context, or levels (paid tiers). Or pass dotted paths like ohlcv.close, trend.direction, trend.stage, trend.ma_slopes.ma_8, trend.ma_slopes.ma_20, trend.ma_slopes.ma_40, trend.ma_slopes.ma_50, trend.ma_slopes.ma_100, trend.ma_slopes.ma_200, trend.moving_average_values.ma_8, trend.ma_crossover_event, trend.direction_meta, trend.distance_from_ma_band.ma_40, trend.volume_confirmation, momentum.rsi, momentum.rsi_zone, momentum.stochastic_k, momentum.stochastic_d, momentum.stochastic_zone, momentum.xtrm_score, momentum.divergence_detected, momentum.divergence_type, momentum.macd_state, patterns.bull_flag, patterns.bull_flag_breakout, patterns.bear_flag, patterns.bear_flag_breakdown, patterns.ascending_triangle, patterns.rising_wedge, volatility.squeeze_active, volatility.squeeze_days, volatility.regime_trend, volume.climax_detected, volume.climax_type, volume.accumulation_state, volume.price_direction_on_volume, support_level.level_price, support_level.status_meta, resistance_level.level_price, sector_context.rsi_zone, sector_context.trend, sector_context.agreement, sector_context.asset_vs_sector_rsi, sector_context.asset_vs_sector_trend, sector_context.oversold_count, sector_context.valuation_zone, fundamentals.pe_ratio, fundamentals.valuation_zone, fundamentals.growth_zone, fundamentals.free_cash_flow, fundamentals.earnings_proximity, fundamentals.earnings_proximity_basis, fundamentals.last_earnings_surprise, fundamentals.analyst_consensus, fundamentals.analyst_consensus_direction, fundamentals.valuation_percentile, fundamentals.pe_vs_historical_zone, fundamentals.pe_vs_sector_zone, fundamentals.insider_activity, fundamentals.insider_activity.zone, fundamentals.insider_activity.net_direction, levels, levels.support_levels, levels.resistance_levels. trend.stage is populated on weekly snapshots when stage evidence is sufficient. Event field names should prefer full schema names such as momentum_rsi_zone, extremes_condition, trend_stage, pattern_bull_flag, pattern_ascending_triangle, pattern_rising_wedge, trend_ma8_slope through trend_ma200_slope, trend_ma_crossover_event, trend_distance_ma40, fundamentals_valuation_zone, fundamentals_free_cash_flow, insider_zone, sector_rsi_zone, momentum_divergence_detected, and fundamentals_analyst_consensus."
    },
    "meta": {
      "type": "boolean",
      "description": "Snapshot and history modes only. Add true to include sibling _meta / status_meta stability objects across the response. Explicit *_meta field paths in fields still work without this flag."
    },
    "field": {
      "type": "string",
      "description": "Band field name for event queries (e.g. momentum_rsi_zone, extremes_condition, trend_direction, trend_stage, pattern_bull_flag, pattern_ascending_triangle, pattern_rising_wedge, trend_ma8_slope through trend_ma200_slope, trend_ma_crossover_event, trend_distance_ma40, fundamentals_valuation_zone, fundamentals_free_cash_flow, insider_zone, sector_rsi_zone, momentum_divergence_detected, fundamentals_analyst_consensus). When provided, returns band transition history instead of a snapshot."
    },
    "band": {
      "type": "string",
      "description": "Filter events to a specific band value (e.g. deep_oversold, strong_uptrend, stage_2_growth). For MA distance event fields such as trend_distance_ma40, grouped aliases above and below are also supported. Only used with field."
    },
    "sample": {
      "type": "string",
      "enum": [
        "even"
      ],
      "description": "Date range mode only. Use 'even' to evenly distribute snapshots across the full start/end range."
    },
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 50,
      "description": "For event mode: max results (1-50), returned newest-first by default. For sample=even date ranges: requested sampled rows, capped by plan (Free 3, Plus 10, Pro 50)."
    },
    "before": {
      "type": "string",
      "description": "Return events before this date (YYYY-MM-DD). Only used with field."
    },
    "after": {
      "type": "string",
      "description": "Return events after this date (YYYY-MM-DD). Only used with field."
    },
    "stats": {
      "type": "boolean",
      "description": "Event mode only. Add true to return aggregate stats instead of raw event rows."
    },
    "context_ticker": {
      "type": "string",
      "description": "Cross-asset correlation: a second ticker to filter against (e.g. SPY). Requires context_field and context_band. Plus/Pro only."
    },
    "context_field": {
      "type": "string",
      "description": "Band field to check on the context ticker (e.g. trend_direction, trend_stage, or trend_distance_ma40). Must be provided with context_ticker and context_band."
    },
    "context_band": {
      "type": "string",
      "description": "Only return events where the context ticker was in this band (e.g. downtrend). For MA distance context fields, grouped aliases above and below are also supported. Must be provided with context_ticker and context_field."
    }
  },
  "required": [
    "ticker"
  ],
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}

Ausgabe-Schema

{
  "type": "object",
  "properties": {
    "data": {
      "description": "The TickerDB API response payload for this tool call."
    }
  },
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢get_ohlcv(ticker, timeframe, start, end, limit, ...)

Get stored end-of-day OHLCV candles for a stock, ETF, or crypto ticker, daily or weekly. Use this for exact-return calculations, charts, and backtests after get_summary identifies a setup. Results are paginated; pass next_cursor back as cursor to continue. Equity and ETF bars are split-and-dividend adjusted; crypto bars are unadjusted. Credit cost is 1 credit per 100 bars returned, rounded up, with a 1 credit minimum.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "ticker": {
      "type": "string",
      "description": "Ticker symbol, e.g. AAPL, BTCUSD, SPY"
    },
    "timeframe": {
      "type": "string",
      "enum": [
        "daily",
        "weekly"
      ],
      "description": "Candle timeframe. Default: daily. Weekly candles cover Monday-Sunday and are dated by the Sunday week end, matching get_summary with timeframe=weekly. The in-progress week is not returned."
    },
    "start": {
      "type": "string",
      "description": "Inclusive start date (YYYY-MM-DD). Compared against the candle date, so for weekly this is the Sunday week end. Lookback is limited by plan."
    },
    "end": {
      "type": "string",
      "description": "Inclusive end date (YYYY-MM-DD). Compared against the candle date."
    },
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 1000,
      "description": "Maximum candles to return (1-1000). Default: 100."
    },
    "order": {
      "type": "string",
      "enum": [
        "asc",
        "desc"
      ],
      "description": "Sort by candle date. Default: desc."
    },
    "cursor": {
      "type": "string",
      "description": "Exclusive date cursor from next_cursor for pagination (YYYY-MM-DD)."
    }
  },
  "required": [
    "ticker"
  ],
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}

Ausgabe-Schema

{
  "type": "object",
  "properties": {
    "data": {
      "description": "The TickerDB API response payload for this tool call."
    }
  },
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢get_search(filters, fields, sort_by, sort_direction, timeframe, ...)

Search for assets matching filter criteria, including categorical states (e.g. oversold assets, strong uptrends, bull/bear flag setups, triangle or wedge setups, free-cash-flow surplus or burn, recent golden crosses, weekly stage 2 assets near the 40w MA with high volume, volatility squeeze active, volume climax detected, insider buying zone, sector-aligned breakouts) or rankings by a field such as market_cap on a historical date. Pass filters as a JSON-encoded array of {field, op, value} objects. Use get_schema to discover valid field names; fields use clean flat names for raw values such as pe_ratio, ma8, ma200, momentum_rsi, momentum_stochastic_k, and momentum_stochastic_d (aliases rsi, stochastic_k, stochastic_d accepted; all three are 0-100, null while lookbacks form, filterable and sortable, available for stocks, ETFs, and crypto), and full expanded names for semantic fields such as momentum_rsi_zone, pattern_bull_flag, pattern_bull_flag_breakout, pattern_bear_flag_breakdown, pattern_ascending_triangle, pattern_rising_wedge, trend_ma_crossover_event, trend_distance_ma40, trend_stage, fundamentals_free_cash_flow, insider_zone, sector_agreement, volatility_squeeze_active, volume_climax_detected, fundamentals_analyst_consensus, and fundamentals_earnings_proximity, fundamentals_earnings_proximity_basis. Use fields to control returned columns and sort_by to rank results server-side.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "filters": {
      "type": "string",
      "description": "JSON-encoded filter array. Each filter: {\"field\": \"column_name\", \"op\": \"eq|neq|in|gt|gte|lt|lte\", \"value\": \"...\"}. Example: [{\"field\": \"momentum_rsi_zone\", \"op\": \"in\", \"value\": [\"oversold\", \"deep_oversold\"]}, {\"field\": \"sector\", \"op\": \"eq\", \"value\": \"Technology\"}]"
    },
    "fields": {
      "type": "string",
      "description": "JSON-encoded array of column names to return. Example: [\"ticker\", \"sector\", \"market_cap\", \"pe_ratio\", \"trend_stage\", \"ma40\", \"trend_ma50_slope\", \"trend_ma_crossover_event\", \"trend_distance_ma40\", \"pattern_bull_flag\", \"pattern_bull_flag_breakout\", \"pattern_bear_flag_breakdown\", \"pattern_ascending_triangle\", \"fundamentals_free_cash_flow\", \"volume_ratio_band\", \"insider_zone\", \"sector_agreement\", \"volatility_squeeze_active\", \"volume_climax_detected\", \"fundamentals_analyst_consensus\", \"fundamentals_earnings_proximity\", \"fundamentals_earnings_proximity_basis\"]. Omit to get a default core subset: ticker, asset_class, sector, market_cap, market_cap_tier, performance, trend_direction, trend_ma20_slope, trend_ma_compression_band, trend_ma_crossover_event, momentum_rsi_zone, extremes_condition, extremes_condition_rarity, volatility_regime, volume_ratio_band, pattern_bull_flag, pattern_bull_flag_breakout, pattern_bear_flag, pattern_bear_flag_breakdown, pattern_ascending_triangle, pattern_descending_triangle, pattern_symmetrical_triangle, pattern_rising_wedge, pattern_falling_wedge, fundamentals_valuation_zone, range_position. Request fundamentals_free_cash_flow explicitly when you need the stock-only free cash flow burn/surplus band. Request ma8 through ma200 for raw MA values and trend_ma8_slope through trend_ma200_slope for the full MA slope set. Use [\"*\"] for all fields. Specify fields to reduce token usage. trend_stage is weekly-only and should be requested with timeframe=weekly. Insider fields (insider_zone, insider_net_direction) and sector context fields (sector_rsi_zone, sector_trend, sector_agreement) are available on paid tiers."
    },
    "sort_by": {
      "type": "string",
      "description": "Column name to sort results by (e.g. \"market_cap\", \"pe_ratio\", \"extremes_condition_percentile\", \"fundamentals_valuation_percentile\", \"volume_percentile\", \"sector_oversold_count\", \"sector_breakout_count\"). Must be a valid field name from the schema. Server-side sorting avoids pulling extra fields for client-side ranking."
    },
    "sort_direction": {
      "type": "string",
      "enum": [
        "asc",
        "desc"
      ],
      "description": "Sort direction. Default: desc. Use 'asc' for lowest-first (e.g. cheapest valuation percentile)."
    },
    "timeframe": {
      "type": "string",
      "enum": [
        "daily",
        "weekly"
      ],
      "description": "Analysis timeframe. Default: daily"
    },
    "date": {
      "type": "string",
      "description": "Historical snapshot date (YYYY-MM-DD). Omit for latest per asset class."
    },
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 500,
      "description": "Max results to return. Tier-gated: Starter 25, Plus 100, Pro 500. Default: 20"
    }
  },
  "required": [
    "filters"
  ],
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}

Ausgabe-Schema

{
  "type": "object",
  "properties": {
    "data": {
      "description": "The TickerDB API response payload for this tool call."
    }
  },
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢get_schema

Get the schema of all available fields and their valid band values. Use this when the user asks 'what fields are available?', 'what bands does momentum_rsi_zone have?', 'what sectors exist?', or when you need to validate field/band names before calling get_summary with event parameters or get_search with filters.

Eingabe-Schema

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}

Ausgabe-Schema

{
  "type": "object",
  "properties": {
    "data": {
      "description": "The TickerDB API response payload for this tool call."
    }
  },
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢get_account

Get your account details including current plan tier, monthly credit limits, and current usage. Response includes tier, limits (monthly_requests, overage_enabled, watchlist_limit, search_results, webhook_urls, history_days), and usage (monthly_requests_used, monthly_requests_remaining, credit_balance for pay-per-use accounts). Also returns scheduled_tier and scheduled_change_at if a plan change is pending.

Eingabe-Schema

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}

Ausgabe-Schema

{
  "type": "object",
  "properties": {
    "data": {
      "description": "The TickerDB API response payload for this tool call."
    }
  },
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢get_watchlist

Get analytical summaries for every ticker on the user's saved watchlist. This supports requests about the user's watchlist, tracked stocks, portfolio tickers, or an overview of tracked assets. Each item includes trend, momentum, volatility, volume, extremes, support/resistance prices, and a notable_changes array of human-readable day-over-day change alerts (e.g. 'entered deep_oversold', 'volume spike', 'trend reversed to downtrend', 'earnings within days', 'squeeze activated', 'MA crossover: golden cross'). Additional per-item fields include squeeze_active, squeeze_days, climax_detected, climax_type, divergence_detected, divergence_type. Plus/Pro plans also return analyst_consensus, earnings_proximity, growth_zone, free_cash_flow. Pro plans also return insider_activity and insider_net_direction. Band fields include _meta stability objects on Plus and Pro plans. Use this only for questions that span the whole tracked set; for a question about one specific ticker use get_summary instead, even if that ticker is on the watchlist. When the question is only whether anything changed, prefer get_watchlist_changes: it returns just the deltas, whereas this returns a full summary per ticker and grows large on a watchlist of many assets. Use add_to_watchlist to save tickers first; an empty watchlist means the user has not saved any tickers yet, not that the lookup failed.

Eingabe-Schema

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}

Ausgabe-Schema

{
  "type": "object",
  "properties": {
    "data": {
      "description": "The TickerDB API response payload for this tool call."
    }
  },
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢get_watchlist_changes(timeframe)

Get field-level state changes for all tickers on the user's saved watchlist since the last pipeline run. Supports daily day-over-day and weekly week-over-week comparisons. Each change object includes stability metadata such as stability, periods_in_current_state, flips_recent, and flips_lookback when available. Stability metadata requires a Plus or Pro plan. Prefer this over get_watchlist for monitoring questions such as whether anything moved, turned bearish, or became overbought, and for tracking a watchlist over time: it returns only what changed, while get_watchlist returns full summaries for every tracked ticker and is far larger on a big watchlist. Use get_watchlist when the current state of the whole list is needed rather than just the deltas. This is the only way to get week-over-week changes; the notable_changes array on get_watchlist is day-over-day only.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "timeframe": {
      "type": "string",
      "enum": [
        "daily",
        "weekly"
      ],
      "description": "Change comparison period. daily = day-over-day, weekly = week-over-week. Default: daily"
    }
  },
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}

Ausgabe-Schema

{
  "type": "object",
  "properties": {
    "data": {
      "description": "The TickerDB API response payload for this tool call."
    }
  },
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟡add_to_watchlist(tickers)

Add tickers to the user's saved watchlist. Duplicates are skipped. Only call this when the user explicitly asks to track, save, or watch a ticker; do not add tickers just because they came up in conversation. The watchlist is capped by the plan's watchlist_limit (see get_account), so the request can be rejected or accepted only in part. Report back which tickers the response actually confirms rather than assuming every requested ticker was added.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "tickers": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Array of ticker symbols to add, e.g. [\"AAPL\", \"MSFT\", \"BTCUSD\"]"
    }
  },
  "required": [
    "tickers"
  ],
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}

Ausgabe-Schema

{
  "type": "object",
  "properties": {
    "data": {
      "description": "The TickerDB API response payload for this tool call."
    }
  },
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🔴remove_from_watchlist(tickers)

Remove tickers from the user's saved watchlist. Only call this when the user explicitly asks to stop tracking, remove, or drop a ticker; never prune the watchlist on your own initiative. Removal only stops tracking and can be undone with add_to_watchlist.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "tickers": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Array of ticker symbols to remove, e.g. [\"MSFT\"]"
    }
  },
  "required": [
    "tickers"
  ],
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}

Ausgabe-Schema

{
  "type": "object",
  "properties": {
    "data": {
      "description": "The TickerDB API response payload for this tool call."
    }
  },
  "additionalProperties": false,
  "$schema": "http://json-schema.org/draft-07/schema#"
}

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