mcp server
TickerDB
Pre-computed market data that improves agent reasoning, reduces token usage, and replaces pipelines.
Description as published by the maintainer. Source
- version 1.8.6
- active
active — Most recent push to the repository was 2026-08-06.
What this server can do
9 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.
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. Required: tickers.
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.
get_ohlcv(end, limit, order, start, cursor, ticker, timeframe)- 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. Required: ticker.
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.
get_search(date, limit, fields, filters, sort_by, timeframe, sort_direction)- 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, and ma200, 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. Required: filters.
get_summary(end, band, date, meta, after, field, limit, start, stats, before, fields, sample, ticker, timeframe, context_band, context_field, context_ticker)- 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 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. Summary keeps sibling _meta objects off by default; set meta=true or request explicit *_meta fields when paid-tier stability metadata is needed. Required: ticker.
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.
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.
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. Required: tickers.
Last successful function declaration observed on . Source: https://mcp.tickerdb.com/mcp. We list what the server declared; we do not call any of these functions.
Endpoint status observed on . Source: https://mcp.tickerdb.com/mcp.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| GitHub stars | 3 | Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. | cumulative, all time | GitHub | |
| Last commit | 2026-08-06 | Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. | point in time | GitHub | |
| Open issues | 4 | Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. | as of fetch | GitHub | |
| Package downloads | 173 downloads | Package downloads from the npm registry in this window. Includes continuous integration runs, mirrors and automated installs, so it overstates the number of human users. | 2026-07-30 to 2026-08-05 | npm | |
| Latest published version | 1.8.6 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-07-09 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| License | MIT | Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. | as of fetch | GitHub | |
| First listed in the MCP Registry | 2026-07-09 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| repository status | active | The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. | as of fetch | GitHub | |
| mcp tools declared | 9 tools | Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. | as of probe | mcp.tickerdb.com | |
| mcp endpoint status | ok | The server listed 9 functions when asked. | as of probe | mcp.tickerdb.com |
Where to get it
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These share tags the maintainers applied themselves, such as crypto, finance, stocks. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.
This is not a recommendation and not a test result. It is a map of what the authors said their work is about.
How the author describes it
Topics the maintainer set on GitHub: ai, chatgpt, claude, crypto, finance, mcp, model-context-protocol, openclaw, stocks, tickerdb.
This record as data
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