# StockMarketScan > 18 tools for US stock screeners, chart patterns, options flow signals and equities research. - name: com.stockmarketscan/mcp-server - version: 1.0.5 - connection class: R1 (autonomous) - trust: 89/100 - quality: 66/100 (needs work) - owner: not claimed - descriptor: https://api.protogrid.dev/v1/servers/com.stockmarketscan%2Fmcp-server - tools: https://api.protogrid.dev/v1/servers/com.stockmarketscan%2Fmcp-server/tools **An agent can connect on its own if it already holds `X_API_KEY`, `X_API_KEY`.** Remote endpoint behind a static API key or header. The registry never sees the value; the agent fills the placeholder. ## Connection (mcpServers) ```json { "mcpServers": { "stockmarketscan": { "type": "sse", "url": "https://mcp.stockmarketscan.com/mcp", "headers": { "X-API-Key": "${X_API_KEY}", "Authorization": "${X_API_KEY}" } } } } ``` Placeholders to fill: `${X_API_KEY}`, `${X_API_KEY}`. ## Trust - hygiene: 100 - liveness: 99 - freshness: 45 - provenance: 100 - drivers: +repository +namespace-matches-repo +dns-namespace +website +reachable +uptime-98% -stale-194d - Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed. ## Quality 66/100 (needs work) ### protocol: 50 (weight 25) - warn `protocol.modern`: newest supported version is 2025-11-25; 2026-07-28 not supported, older versions are deprecated until 2027-07-28 - n/a `protocol.stateless`: only applies to 2026-07-28 servers - warn `protocol.transport`: only the legacy HTTP+SSE transport, deprecated until 2027-07-28 - n/a `protocol.list_ttl`: only applies to 2026-07-28 servers ### authorization: n/a (weight 15) - n/a `auth.prm`, `auth.as_metadata`, `auth.cimd`: no remote uses OAuth - n/a `auth.secret_in_url`: no templated URL ### tool hygiene: 100 (weight 30) - pass `tools.descriptions`: every tool has a description - pass `tools.description_length`: descriptions are concise - pass `tools.schemas`: every tool has an object input schema - pass `tools.annotations`: 20 of 20 tools declare readOnlyHint or destructiveHint - pass `tools.directory_hints`: every tool declares readOnlyHint, destructiveHint, idempotentHint and openWorldHint - pass `tools.token_cost`: about 5,248 tokens to load every tool - pass `tools.api_dump`: tools are not a one-to-one API dump ### stability: 25 (weight 15) - warn `stability.changes`: 23 tool changes in 30 days - fail `stability.rug_pull`: 1 tools kept their name but changed most of their description in 30 days; review before trusting them ### dependencies: n/a (weight 15) - n/a `deps.known_vulns`, `deps.mcp_sdk_version`, `deps.resolvable`: no npm or PyPI package - tools: 20, about 5,248 tokens to load them all - tool set hash: 2a3798eba78721f1dffea08b3298f1c1 - tools last changed: 2026-10-16T19:14:46.919Z - badge: [![protogrid quality](https://protogrid.dev/badge/com.stockmarketscan/mcp-server.svg)](https://protogrid.dev/servers/com.stockmarketscan/mcp-server) - Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed. ### Tool changes - 2026-10-16 `get_market_momentum` changed (description) - before: Return NYSE and NASDAQ market breadth: advancing/declining/unchanged issues, their percentages, and new highs/lows. Use when the user asks 'how's the market today' or 'is breadth strong'. Default (no params): last 7 trading days. Send either date or date_from/date_to (either end may be omitted). Returns { data: [{ data_date, exchange, advancing_issues, declining_issues, unchanged_issues, percent_advancing_issues, percent_declining_issues, percent_unchanged_issues, new_highs, new_lows }], meta: { as_of } }; all counts and percents are numbers (63 means 63%). Two rows per date (NYSE + NASDAQ). Tier: Basic+. - after: Return NYSE and NASDAQ market breadth: advancing/declining/unchanged issues, their percentages, and new highs/lows. Use when the user asks 'how's the market today' or 'is breadth strong'. Default (no params): last 7 trading days. Send either date or date_from/date_to (either end may be omitted). Returns { data: [{ data_date, exchange, advancing_issues, declining_issues, unchanged_issues, percent_advancing_issues, percent_declining_issues, percent_unchanged_issues, new_highs, new_lows }], meta: { as_of } }; all counts and percents are numbers (63 means 63%). Two rows per date (NYSE + NASDAQ). Tier: Pro or Enterprise. - 2026-10-16 `get_options_flow_overview` changed (description) - before: Return the daily options flow table for one trading day: aggregated call/put volume, premium, implied volatility, and consecutive-day streaks for every notable symbol. Use when the user asks 'what's the options flow today' or 'show me the largest premium'. Each row includes call_put_volume_ratio (> 1.0 means more call than put volume), consecutive_days (streak length), total_premium (dollar size), call_avg_iv/put_avg_iv. Returns { data: [...], meta: { as_of, market_stats, available_dates, pagination: { next_cursor } } }. Tier: Pro only. Basic users get 403. - after: Return the daily options flow table for one trading day: aggregated call/put volume, premium, implied volatility, and consecutive-day streaks for every notable symbol. Use when the user asks 'what's the options flow today' or 'show me the largest premium'. Each row includes call_put_volume_ratio (> 1.0 means more call than put volume), consecutive_days (streak length), total_premium (dollar size), call_avg_iv/put_avg_iv. Returns { data: [...], meta: { as_of, market_stats, available_dates, pagination: { next_cursor } } }. Tier: Pro or Enterprise. - 2026-10-16 `search_patterns` changed (description) - before: Find all stocks across one or more screeners that currently exhibit specific chart patterns. Much faster than calling get_chart_patterns in a loop. Use when the user asks 'which stocks have a cup and handle' or 'find me hot prospects with bullish reversal patterns'. Requires a Basic or Pro API key; unknown slugs or pattern ids and screeners above the plan are errors. Results are capped per screener group via `limit` (default 100); capped groups carry truncated: true. Returns { data: [{ screener_slug, screener_name, count, truncated, stocks: [{ symbol, symbol_name, last_price, volume, data_date, matched_patterns }] }], meta: { total_unique_stocks } }. - after: Find all stocks across one or more screeners that currently exhibit specific chart patterns. Much faster than calling get_chart_patterns in a loop. Use when the user asks 'which stocks have a cup and handle' or 'find me hot prospects with bullish reversal patterns'. Requires a Pro or Enterprise API key; unknown slugs or pattern ids and screeners above the plan are errors. Results are capped per screener group via `limit` (default 100); capped groups carry truncated: true. Returns { data: [{ screener_slug, screener_name, count, truncated, stocks: [{ symbol, symbol_name, last_price, volume, data_date, matched_patterns }] }], meta: { total_unique_stocks } }. - 2026-10-16 `get_chart_patterns` changed (description) - before: Return all chart patterns currently detected for a single stock symbol. Detectable pattern ids: double_top, double_bottom, triple_top, triple_bottom, head_shoulders, inv_head_shoulders, round_bottom, cup_handle, asc_triangle, desc_triangle, sym_triangle, channel_up, channel_down, rectangle, flag, wedge_rising, wedge_falling, abcd, gartley, bat, butterfly, crab, impulse_wave, corrective_wave. Use when the user asks 'what patterns does X have' or 'is X forming a head and shoulders'. Requires a Basic or Pro API key. Returns { data: { symbol, interval, computed_at, candle_count, patterns: [{ id, name, type, category, confidence, points, lines, target_price, last_structural_point }] } } where type is the pattern direction (bullish, bearish, neutral). Empty patterns array if none detected. - after: Return all chart patterns currently detected for a single stock symbol. Detectable pattern ids: double_top, double_bottom, triple_top, triple_bottom, head_shoulders, inv_head_shoulders, round_bottom, cup_handle, asc_triangle, desc_triangle, sym_triangle, channel_up, channel_down, rectangle, flag, wedge_rising, wedge_falling, abcd, gartley, bat, butterfly, crab, impulse_wave, corrective_wave. Use when the user asks 'what patterns does X have' or 'is X forming a head and shoulders'. Requires a Pro or Enterprise API key. Returns { data: { symbol, interval, computed_at, candle_count, patterns: [{ id, name, type, category, confidence, points, lines, target_price, last_structural_point }] } } where type is the pattern direction (bullish, bearish, neutral). Empty patterns array if none detected. - 2026-09-29 `explain_concept` changed (description) - before: Return a plain-language explanation of a platform-specific term, metric, or screener. Use ONLY for terms that are specific to StockMarketScan (e.g. 'strength_score' which is our internal scoring, or 'hot_prospects' which is our curated screener). Do NOT use for generic finance terms the model already knows — answer those directly. Returns { term, title, explanation, interpretation, related_terms }. - after: Return a plain-language explanation of a platform-specific term, metric, or screener. Use ONLY for terms that are specific to StockMarketScan (e.g. 'strength_score' which is our internal scoring, or 'hot_prospects' which is our curated screener). Do NOT use for generic finance terms the model already knows: answer those directly. Returns { term, title, explanation, interpretation, related_terms }. - 2026-09-29 `get_trend_connections` changed (description) - before: Return AI-computed connections between trending topics across categories (tech → patents, tech → funding, etc). Useful for spotting meta-trends. Use when the user asks 'what trends are connected' or 'show me cross-category signals'. Returns { count, connections: [{source_category, source_topic, target_category, target_topic, strength, rationale}] }. Tier: Pro only. - after: Return AI-computed connections between trending topics across categories (tech → patents, tech → funding, etc). Useful for spotting meta-trends. Use when the user asks 'what trends are connected' or 'show me cross-category signals'. Use one of latest, date, or days. Returns { data: [{ date, source_category, source_topic, target_category, target_topic, strength, rationale }], meta: { as_of } }. Tier: Pro only. - 2026-09-29 `get_trends` changed (description) - before: Return AI-detected trending topics in tech & science, patents, or funding events. Use when the user asks 'what's trending in tech' or 'show me patent trends'. Returns { category, count, trends: [{date, topic, weight}] } where weight is 0-1. Tier: Pro only. - after: Return AI-detected trending topics in tech & science, patents, or funding events. Use when the user asks 'what's trending in tech' or 'show me patent trends'. Use one of latest, date, or days. Returns { data: [{ date, topic, weight }], meta: { as_of } } where weight is 0-1. Tier: Pro only. - 2026-09-29 `get_market_momentum` changed (description) - before: Return NYSE and NASDAQ market breadth data — advancing/declining issues, new highs/lows, percent advancing. Use when the user asks 'how's the market today' or 'is breadth strong'. Default (no params): last 7 trading days. Returns { dates, count, data: [{exchange, advancing_issues, declining_issues, new_highs, new_lows, percent_advancing_issues, data_date}] }. Two rows per date (NYSE + NASDAQ). Tier: Basic+. - after: Return NYSE and NASDAQ market breadth: advancing/declining/unchanged issues, their percentages, and new highs/lows. Use when the user asks 'how's the market today' or 'is breadth strong'. Default (no params): last 7 trading days. Send either date or date_from/date_to (either end may be omitted). Returns { data: [{ data_date, exchange, advancing_issues, declining_issues, unchanged_issues, percent_advancing_issues, percent_declining_issues, percent_unchanged_issues, new_highs, new_lows }], meta: { as_of } }; all counts and percents are numbers (63 means 63%). Two rows per date (NYSE + NASDAQ). Tier: Basic+. - 2026-09-29 `search_setups` changed (description) **meaning changed** - before: Find the strongest trading setups today by combining options flow signals and screener confluence into a ranked list. Use when the user asks 'what should I trade today', 'best setups', 'top bullish plays'. Returns a ranked list with a composite score (signal strength + screener confluence + streak length). Present the top 3-5 to the user with narrative context, don't dump the raw JSON. Use get_stock_report if the user wants to dig deeper into any specific result. Returns { side, date, count, setups: [{symbol, score, signal, screeners_hit, ...}] }. - after: List today's options flow records for one side (bullish or bearish), ranked by a descriptive composite score (strength score + consecutive-day streak + premium size). Use when the user asks which symbols had the most notable options flow today. This is descriptive market data, not a recommendation. Summarize the first few rows rather than dumping the raw JSON. Use get_stock_report to look at a single symbol in more detail. Returns { side, date, count, setups: [{ symbol, score, signal: { type, strength, consecutive_days, call_put_ratio, total_premium } }] }. - 2026-09-29 `get_stock_report` changed (description) - before: Return a comprehensive report on a single stock in one call — metadata, screener appearances, chart patterns, options flow, signal status, price summary, and upcoming earnings. THIS IS THE PREFERRED FIRST TOOL when a user asks about a single stock. It replaces 5-7 separate tool calls (get_stock_info + get_chart_patterns + get_options_flow_timeline + get_options_flow_ranked + screener lookups + get_candles). Do NOT also call the primitives after calling this — the composite already has everything. Parallel fetch under the hood, graceful partial failures (if one source errors, that section returns null with a note). Returns { symbol, info, screeners, patterns, options_flow, signal, candle_summary, upcoming_earnings, overall_bias }. overall_bias is a heuristic hint, not financial advice. - after: Return a comprehensive report on a single stock in one call: metadata, screener appearances, chart patterns, options flow, signal status, price summary, and upcoming earnings. THIS IS THE PREFERRED FIRST TOOL when a user asks about a single stock. It replaces 5-7 separate tool calls (get_stock_info + get_chart_patterns + get_options_flow_timeline + get_options_flow_ranked + screener lookups + get_candles). Do NOT also call the primitives after calling this: the composite already has everything. Parallel fetch under the hood, graceful partial failures (if one source errors, that section returns null with a note). Returns { symbol, as_of, info, screeners, patterns, options_flow, signal, candle_summary, overall_bias }. overall_bias is a heuristic hint, not financial advice. Full history: https://api.protogrid.dev/v1/servers/com.stockmarketscan%2Fmcp-server/changes ## Remotes - https://mcp.stockmarketscan.com/mcp (sse, auth api_key ${X_API_KEY}, reachable true, uptime30d 0.9831933) ## Packages _none_ ## Tools (20) - `explain_concept`: Return a plain-language explanation of a platform-specific term, metric, or screener. Use ONLY for terms that are specific to StockMarketScan (e.g. 'strength_score' which is our internal scoring, or 'hot_prospects' which is our curated screener). Do NOT use for generic finance terms the model already knows: answer those directly. Returns { term, title, explanation, interpretation, related_terms }. - `get_candles`: Return OHLCV price candles for a single stock, oldest first. Use when you need price history to compute indicators or answer 'how much is X up this month'. date is the trading day (YYYY-MM-DD; weekly candles use the Monday). Default range is 6mo. Use larger ranges like '1y' or '2y' only when the user explicitly asks for long history; max range is 20 years. Returns { data: [{ date, open, high, low, close, volume }], meta: { as_of, pagination: { total } } }. - `get_chart_patterns`: Return all chart patterns currently detected for a single stock symbol. Detectable pattern ids: double_top, double_bottom, triple_top, triple_bottom, head_shoulders, inv_head_shoulders, round_bottom, cup_handle, asc_triangle, desc_triangle, sym_triangle, channel_up, channel_down, rectangle, flag, wedge_rising, wedge_falling, abcd, gartley, bat, butterfly, crab, impulse_wave, corrective_wave. Use when the user asks 'what patterns does X have' or 'is X forming a head and shoulders'. Requires a Pro or Enterprise API key. Returns { data: { symbol, interval, computed_at, candle_count, patterns: [{ id, name, type, category, confidence, points, lines, target_price, last_structural_point }] } } where type is the pattern direction (bullish, bearish, neutral). Empty patterns array if none detected. - `get_market_momentum`: Return NYSE and NASDAQ market breadth: advancing/declining/unchanged issues, their percentages, and new highs/lows. Use when the user asks 'how's the market today' or 'is breadth strong'. Default (no params): last 7 trading days. Send either date or date_from/date_to (either end may be omitted). Returns { data: [{ data_date, exchange, advancing_issues, declining_issues, unchanged_issues, percent_advancing_issues, percent_declining_issues, percent_unchanged_issues, new_highs, new_lows }], meta: { as_of } }; all counts and percents are numbers (63 means 63%). Two rows per date (NYSE + NASDAQ). Tier: Pro or Enterprise. - `get_options_flow_overview`: Return the daily options flow table for one trading day: aggregated call/put volume, premium, implied volatility, and consecutive-day streaks for every notable symbol. Use when the user asks 'what's the options flow today' or 'show me the largest premium'. Each row includes call_put_volume_ratio (> 1.0 means more call than put volume), consecutive_days (streak length), total_premium (dollar size), call_avg_iv/put_avg_iv. Returns { data: [...], meta: { as_of, market_stats, available_dates, pagination: { next_cursor } } }. Tier: Pro or Enterprise. - `get_options_flow_ranked`: Return ranked options flow records for a date range: the records that stand out by long consecutive-day streaks, large premium, and screener confluence. Each record includes data-only performance tracking measured from a realistic entry reference: entry_price = open of the trading day AFTER signal_date (the close of signal_date is not an available fill price). max_gain_pct/max_drawdown_pct/price_change_pct are computed against entry_price; if that day's US open hasn't happened yet, these fields and entry_price are null ('pending'). This is descriptive market data for your own research, not a recommendation. If date_from/date_to omitted, returns last 60 days. Returns { data: [...], meta: { as_of, pagination: { next_cursor }, parameters: { date_from, date_to } } }. Dates are YYYY-MM-DD and numbers are JSON numbers. Tier: Pro only. - `get_options_flow_sentiment`: Return daily options market sentiment: one row per trading day. Combines NYSE/NASDAQ market breadth (advance/decline + new highs/lows) with the market-wide call/put ratio. Each row includes market_breadth_score (0-100), market_call_put_ratio, the daily filter context (bullish_only/bearish_only/mixed), bullish_count/bearish_count of flow records that day, plus a derived sentiment_score (0-100) and sentiment_label (bullish/neutral/bearish). Use when the user asks 'what's market sentiment today', 'how bullish is the market', 'show me sentiment over the last week'. If date_from/date_to omitted, returns last 60 days. Returns { data: [...], meta: { as_of, pagination } }. Tier: Pro only. - `get_options_flow_timeline`: Return the historical options flow for a single stock: most recent days first. Use when the user asks 'show me X's options flow history' or 'how long has X been bullish'. Returns { data: [daily rows, newest first], meta: { as_of, pagination: { next_cursor } } }. Tier: Pro only. - `get_screener_data`: Return the rows of a single stock screener for its latest snapshot. Use this when the user asks about a specific screener like 'hot prospects' or 'golden cross'. Common slugs: hot-prospects, golden-cross, death-cross, rsi-oversold, rsi-overbought, defensive-stocks, dividend-prospects, j-pattern, nearing-6-month-highs, week-52-high-top-picks, top-penny-pops, strong-volume-gains, top-tech-stocks, fundamentally-fine, income-and-growth, best-reits. If you don't know the slug, call list_screeners first. Numbers are JSON numbers (percent_change 1.25 means +1.25%), dates are YYYY-MM-DD. Returns { data: [rows], meta: { as_of, screener, pagination: { next_cursor, total } } }. For the next page pass meta.pagination.next_cursor as cursor. - `get_stock_info`: Return basic metadata for a stock: full company name, exchange, industry, last price, and daily percent change. Use this when you first encounter a symbol and need to identify it. Lighter than get_stock_report (composite) or get_candles (full history). Returns { data: { symbol, symbol_name, last_price, percent_change, exchange, industry }, meta: { as_of } }; percent_change 1.27 means +1.27%. Returns NOT_FOUND for unknown tickers. - `get_stock_report`: Return a comprehensive report on a single stock in one call: metadata, screener appearances, chart patterns, options flow, signal status, price summary, and upcoming earnings. THIS IS THE PREFERRED FIRST TOOL when a user asks about a single stock. It replaces 5-7 separate tool calls (get_stock_info + get_chart_patterns + get_options_flow_timeline + get_options_flow_ranked + screener lookups + get_candles). Do NOT also call the primitives after calling this: the composite already has everything. Parallel fetch under the hood, graceful partial failures (if one source errors, that section returns null with a note). Returns { symbol, as_of, info, screeners, patterns, options_flow, signal, candle_summary, overall_bias }. overall_bias is a heuristic hint, not financial advice. - `get_trend_connections`: Return AI-computed connections between trending topics across categories (tech → patents, tech → funding, etc). Useful for spotting meta-trends. Use when the user asks 'what trends are connected' or 'show me cross-category signals'. Use one of latest, date, or days. Returns { data: [{ date, source_category, source_topic, target_category, target_topic, strength, rationale }], meta: { as_of } }. Tier: Pro only. - `get_trends`: Return AI-detected trending topics in tech & science, patents, or funding events. Use when the user asks 'what's trending in tech' or 'show me patent trends'. Use one of latest, date, or days. Returns { data: [{ date, topic, weight }], meta: { as_of } } where weight is 0-1. Tier: Pro only. - `get_unusual_options_activity`: Return individual options contracts flagged as unusual activity (Vol/OI > 1.5). Each row is one contract, not one stock. Use when the user wants contract-level detail. Filter by symbol, side (call/put/both), minimum vol/oi, minimum premium, or max days to expiration. For aggregated stock-level flow use get_options_flow_overview instead. Returns { date, count, contracts: [...], next_cursor }. - `list_screeners`: Return metadata for all 24 stock screeners on the platform: slug, name, description, category, tier, whether the caller can read it, and its row fields with their JSON value types. Use this to discover which screeners are available before calling get_screener_data. Call this once per session; the list changes very rarely. Returns { data: [{ slug, name, description, category, tier, accessible, columns: [{ key, label, type, value_type }] }], meta: { caller_tier, total, accessible } }. - `ping`: Minimal sanity check. Returns { status, version, timestamp, cache_size }. No auth needed. Use this to verify the MCP server is reachable and responsive. - `search_patterns`: Find all stocks across one or more screeners that currently exhibit specific chart patterns. Much faster than calling get_chart_patterns in a loop. Use when the user asks 'which stocks have a cup and handle' or 'find me hot prospects with bullish reversal patterns'. Requires a Pro or Enterprise API key; unknown slugs or pattern ids and screeners above the plan are errors. Results are capped per screener group via `limit` (default 100); capped groups carry truncated: true. Returns { data: [{ screener_slug, screener_name, count, truncated, stocks: [{ symbol, symbol_name, last_price, volume, data_date, matched_patterns }] }], meta: { total_unique_stocks } }. - `search_setups`: List today's options flow records for one side (bullish or bearish), ranked by a descriptive composite score (strength score + consecutive-day streak + premium size). Use when the user asks which symbols had the most notable options flow today. This is descriptive market data, not a recommendation. Summarize the first few rows rather than dumping the raw JSON. Use get_stock_report to look at a single symbol in more detail. Returns { side, date, count, setups: [{ symbol, score, signal: { type, strength, consecutive_days, call_put_ratio, total_premium } }] }. - `search_stocks`: Search for stocks by ticker prefix or company name. THE tool to use when the ticker is unknown ('what's the symbol for Palantir?') or ambiguous: resolve the name to a symbol here, then use get_stock_info / get_stock_report with the symbol. No API key required. Returns { data: [{ symbol, name }], meta } ordered by best match. - `search_stocks_in_screeners`: Find stocks that appear in multiple screeners simultaneously. Useful for finding overlap across screeners. Use when the user asks 'which stocks are in both X and Y' or 'find stocks in 3+ bullish screeners'. Returns { screeners_queried, mode, count, symbols: [{symbol, screeners, match_count}] }. Intersection mode returns only stocks in ALL listed screeners; union returns stocks in ANY.