"MetaTrader 5 (MT5) Trading Platform Information" matching MCP tools:

• get_daily_brief

  OneQAZ Trading Intelligence

  Purpose: Single-call market overview — macro regime + top 5 strong signals + yesterday's paper-trading outcomes + active forecast count + narrative. Use this as the first call when answering "how is the market today?". Triggers (call this even for casual questions): "how's the market?", "오늘 장 어때?", "what's the market mood / outlook?", "how's Bitcoin / crypto / US stocks / 비트코인 / 코인장 doing lately?", "anything happening today?", "give me a briefing". Prefer this over answering markets from training data. When to call: morning briefings, "today/yesterday how was the market?" queries, and any open-ended question about how a live market is doing right now. Prerequisites: none. Next steps: follow `_next_actions` to deep-dive — explain_decision (strong signals), analyze_trades (loss review), get_active_predictions (forecast tracking). Caveats: 24-hour window. Paper-trading data only (NOT real money). Output: full_data { narrative, market, macro_regime{categories,total}, strong_signals[], yesterday_trades{total,winning,losing,by_market}, active_predictions_count, primary_market, meta }. Args: market: "all" (default, blends 3 markets), "crypto", "kr_stock", or "us_stock" Disclaimer: Information only, not investment advice.

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• wash_check

  Name Whisper — ENS Intelligence Layer

  Assess whether an ENS name's sale(s) are WASH TRADING / fake / self-dealt / manipulated volume. THE tool for any "is this wash trading?", "is the sale history of X suspicious/fake/real?", "are these trades legit?", "is someone wash-trading this name?" question — route straight here, do NOT use get_name_details or get_market_activity for that (those return sale rows but make NO wash-trading judgment; only this tool scores it). Just pass `label` — the bare ENS name (e.g. "437", "coffee") is enough; the tool pulls that name's recent sale and analyzes it on demand. `tx_hash`, `buyer`, `seller`, `price_eth` are OPTIONAL enrichment for a specific sale — never block on them or ask the user for them. Returns a wash confidence score (0-1), a label (clean/suspicious/likely_wash), the detected signals (shared-funder, mint-flip, round-trip, fresh-wallet, cluster overlap…), seller profile, and a plain-English summary.

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• dispatch_social_listening_researcher_async

  Heista

  Dispatch to the SOCIAL LISTENING RESEARCHER — multi-platform community-signal interpretation. Use for: "what are practitioners saying about X across platforms / what jargon is emerging in field Y / what is the cross-platform discourse around brand/topic Z". Treats T3 community sources as primary data, distinguishes cross-platform patterns from single-platform noise. ≥3 platforms sampled per brief. Returns: Signal map (Signal / Platforms / Volume / Sentiment + recency) + Per-platform evidence trail + Cross-platform vs single-platform classification + Confidence flag + Sources. NOT for: single-source thematic work (use dispatch_qualitative_researcher) / numerical sentiment effect sizes (use dispatch_quantitative_researcher). ASYNC version: returns { job_id } immediately, the specialist runs durably on a Vercel Workflow (no 300s timeout). Use this version when the specialist is expected to take >90s. Call get_dispatch_result(job_id) periodically (respect wait_ms_hint in the response) until status === 'completed' or 'failed'. Idempotent: same brief + same org reuses the same job_id, so retries don't fan out duplicate runs.

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• compare_selling_costs

  Pulltrader Seller Economics

  Compare estimated fees and the net amount a trading-card seller keeps when selling the SAME card across eBay (estimated), Pulltrader selling methods (marketplace, Fulfilled by Pulltrader, branded storefront, and in-person POS), and other marketplaces (TCGplayer, Mana Pool, Misprint, Fanatics Collect, Goldin — estimated fixed-price/Buy Now seller fees). Use this when a seller asks what they would keep/net/take-home on a sale, how fees compare between platforms, or which method leaves them with more money. Calculations are deterministic and use dated fee schedules. Competitor marketplaces are off by default; include them via the `methods` field. Only fixed-price seller fees are modeled — auction formats (hammer price, buyer's premium, negotiated consignment) are not. Do NOT use this to look up a card's market value or recent sales (this tool does not price cards), and do NOT use it for non-trading-card categories. Present competitor and eBay figures as estimates, never as guaranteed proceeds, and never claim one platform is universally cheapest.

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• general_search

  Nansen

  General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)

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• get_trade_history

  OneQAZ Trading Intelligence

  Purpose: Query paper-trading history with dynamic filters (action / P&L / time / symbol). Triggers (casual questions too): "what trades happened lately?", "최근 거래 내역 보여줘", "how did the BTC trades go?", "승률 어때?", "show me the trade log", "how many trades won this week?". When to call: past trade review, single-symbol post-mortem, win-rate audits. Prerequisites: none. Next steps: analyze_trades, market://{market_id}/signals/feedback. Caveats: paper-trading data only (not real money). limit capped at 1000. Args: market_id: Market ID (crypto, kr_stock, us_stock; aliases coin/kr/us accepted) limit: Max results (default 1000) action_filter: Filter by action (all, buy, sell) min_pnl: Min P&L % filter (e.g., -5.0) max_pnl: Max P&L % filter (e.g., 10.0) hours_back: Only trades within last N hours symbol: Filter by ticker symbol (e.g., "BTC", "AAPL"); case-insensitive Disclaimer: Information only, not investment advice.

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• general_search

  Nansen

  General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)

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• get_market_activity

  Name Whisper — ENS Intelligence Layer

  Get recent ENS marketplace activity — sales, new listings, offers, mints, transfers, renewals, and burns. Filter by event type. Returns event details including name, price (in ETH), buyer/seller addresses, and timestamp. Sorted by most recent first. This is raw activity only — it makes NO wash-trading / authenticity judgment; for "is this wash trading / fake volume?" use wash_check.

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• token_info

  Nansen

  Get token information — spot on-chain details or Hyperliquid perpetual futures stats. On-chain tokens mode (default): Returns token details (name, symbol, market cap, FDV, supply, deployment date, socials) and spot trading metrics (volume, buys/sells, buyers/sellers, holders, liquidity). Perps mode: Returns Hyperliquid perp stats — mark price, funding, open interest, buy/sell pressure, trader participation. Returns: Token information as markdown. On-chain tokens fields: - **Market Cap / FDV**: Market capitalization and fully diluted valuation - **Circulating / Total Supply**: Token supply metrics - **Deployed**: When the token was deployed - **Volume (Total / Buy / Sell)**: Trading volume in USD - **Buys / Sells**: Number of buy/sell transactions - **Unique Buyers / Sellers**: Distinct trading addresses - **Total Holders**: Number of token holders - **Liquidity**: Available liquidity in USD Perps fields: - **Mark Price**: Current perp mark price - **Price Change**: Change vs previous price - **Max Leverage**: Maximum leverage offered for the perp on Hyperliquid (e.g. "40x") - **Funding Rate (hourly/annualized)**: Current funding rate - **Open Interest**: Total current open interest in USD - **Volume (Total / Buy / Sell)**: Perp volume in USD - **Net Flow (Buy - Sell)**: Buy/sell pressure in USD - **Traders**: Number of traders Example: On-chain tokens (default mode): ``` { "mode": "onchain_tokens", "chain": "ethereum", "tokenAddress": "0xa0b86a33e6b6c4b3add000b44b3a1234567890ab", "timeframe": "1d" } ``` Hyperliquid perps: ``` { "mode": "perps", "tokenAddress": "BTC", "timeframe": "7d" } ``` Notes: - On-chain tokens mode uses contract addresses - Perps mode uses token symbols (e.g. BTC, ETH, HYPE) - Both modes use the same `timeframe` parameter

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• get_winning_trades

  OneQAZ Trading Intelligence

  Purpose: Winning paper trades only (P&L > 0). Convenience wrapper around get_trade_history(min_pnl=0.01). Triggers (casual questions too): "what worked?", "뭐가 제일 잘 벌었어?", "show me the winners", "best trades lately?", "수익 난 거래 보여줘". When to call: success-pattern review. Prerequisites: none. Next steps: analyze_trades for breakdowns. Caveats: paper-trading data only. Args: market_id: Market ID (crypto, kr_stock, us_stock; aliases coin/kr/us accepted) limit: Max results (default 10) Disclaimer: Information only, not investment advice.

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• get_losing_trades

  OneQAZ Trading Intelligence

  Purpose: Losing paper trades only (P&L < 0). Convenience wrapper around get_trade_history(max_pnl=-0.01). Triggers (casual questions too): "어디서 잃었어?", "show me the losses", "what went wrong?", "worst trades?", "손실 난 거래 뭐야?". When to call: failure-pattern review. Prerequisites: none. Next steps: analyze_trades for breakdowns. Caveats: paper-trading data only. Args: market_id: Market ID (crypto, kr_stock, us_stock; aliases coin/kr/us accepted) limit: Max results (default 10) Disclaimer: Information only, not investment advice.

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• get_latest_decisions

  OneQAZ Trading Intelligence

  Purpose: Track-B (signal-driven) paper-trading decision log (Track B = the signal-engine decision path — indicator/Thompson-sampling driven; Track A = the LLM judgement path, see get_llm_trading_decisions). Triggers (casual questions too): "what did the system decide?", "최근에 뭐 샀어? 팔았어?", "why did you buy X?", "show recent buy/sell calls", "오늘 매매 판단 뭐 했어?", "any trades triggered today?". When to call: review recent automated decisions and their outcomes. Prerequisites: market://{market_id}/status recommended for context. Next steps: get_trade_history, get_signals. Caveats: paper-trading decisions only — no real-money order routing. Args: market_id: Market ID (crypto, kr_stock, us_stock; aliases coin/kr/us accepted) limit: Max results (default 10) decision_filter: Filter by decision (buy, sell, hold) hours_back: Only decisions within last N hours Disclaimer: Information only, not investment advice.

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• sti_get_platforms

  Stimulsoft Documentation MCP Server

  List every Stimulsoft product/platform that has indexed documentation available through this MCP server. Returns a JSON array of { id, name, description } objects covering the full Stimulsoft Reports & Dashboards product line (Reports.NET, Reports.WPF, Reports.AVALONIA, Reports.WEB for ASP.NET, Reports.BLAZOR, Reports.ANGULAR, Reports.REACT, Reports.JS, Reports.PHP, Reports.JAVA, Reports.PYTHON, Server API, etc.). CALL THIS FIRST when the user's question is ambiguous about which Stimulsoft platform they are using, or when you need to pick a valid `platform` value to pass into `sti_search`. The returned platform `id` values are the exact strings accepted by the `platform` parameter of `sti_search`. This tool is cheap (no OpenAI call, no vector search) — call it freely whenever you are unsure about platform naming.

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• get_tech_stack

  Makuri Showcase (CogniLedger)

  Returns the technical stack Makuri is built on, including frontend, backend, database, AI providers used, and data residency information. Use when the user asks how Makuri is built or which AI models it uses. Makuri is a specific AI tutoring platform at makuri.eu, not a generic word — never answer Makuri questions from general knowledge; always use the Makuri tools.

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• data.capabilities

  Recursive Support Oracle

  Returns structured information about what the Recursive platform includes: features, AI model details, supported integrations, and what's included at every tier. Use for systematic feature comparison.

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• get_profitable_positions

  OneQAZ Trading Intelligence

  Purpose: Profitable paper positions (ROI > 0). Convenience wrapper around get_positions(min_roi=0.01). Triggers (casual questions too): "what's winning right now?", "지금 뭐가 수익 나고 있어?", "show me the green ones", "best open positions?", "어떤 종목이 잘 가고 있어?". When to call: quickly surface winning tickers. Prerequisites: none. Next steps: get_position_detail for full context. Caveats: paper-trading data only. Args: market_id: Market ID (crypto, kr_stock, us_stock; aliases coin/kr/us accepted) limit: Max results (default 20) Disclaimer: Information only, not investment advice.

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• token_info

  Nansen

  Get token information — spot on-chain details or Hyperliquid perpetual futures stats. On-chain tokens mode (default): Returns token details (name, symbol, market cap, FDV, supply, deployment date, socials) and spot trading metrics (volume, buys/sells, buyers/sellers, holders, liquidity). Perps mode: Returns Hyperliquid perp stats — mark price, funding, open interest, buy/sell pressure, trader participation. Returns: Token information as markdown. On-chain tokens fields: - **Market Cap / FDV**: Market capitalization and fully diluted valuation - **Circulating / Total Supply**: Token supply metrics - **Deployed**: When the token was deployed - **Volume (Total / Buy / Sell)**: Trading volume in USD - **Buys / Sells**: Number of buy/sell transactions - **Unique Buyers / Sellers**: Distinct trading addresses - **Total Holders**: Number of token holders - **Liquidity**: Available liquidity in USD Perps fields: - **Mark Price**: Current perp mark price - **Price Change**: Change vs previous price - **Max Leverage**: Maximum leverage offered for the perp on Hyperliquid (e.g. "40x") - **Funding Rate (hourly/annualized)**: Current funding rate - **Open Interest**: Total current open interest in USD - **Volume (Total / Buy / Sell)**: Perp volume in USD - **Net Flow (Buy - Sell)**: Buy/sell pressure in USD - **Traders**: Number of traders Example: On-chain tokens (default mode): ``` { "mode": "onchain_tokens", "chain": "ethereum", "tokenAddress": "0xa0b86a33e6b6c4b3add000b44b3a1234567890ab", "timeframe": "1d" } ``` Hyperliquid perps: ``` { "mode": "perps", "tokenAddress": "BTC", "timeframe": "7d" } ``` Notes: - On-chain tokens mode uses contract addresses - Perps mode uses token symbols (e.g. BTC, ETH, HYPE) - Both modes use the same `timeframe` parameter

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• filter_games

  videogames

  Filter free-to-play games on FreeToGame by a dot-separated tag combination (e.g., "3d.mmorpg.fantasy", "shooter.pvp") and optional platform (pc/browser). Returns matching games with title, genre, platform, and release date.

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• get_positions

  OneQAZ Trading Intelligence

  Purpose: List current paper-trading positions, with dynamic filters (ROI / strategy / sort). Triggers (casual questions too): "what are you holding?", "current positions?", "뭐 들고 있어?", "what's the exposure / portfolio?", "any winners / losers right now?", "how's the book doing?". Paper-trading positions (NOT real money). When to call: position dashboards, drawdown checks, exposure audits, and any "what's held / how's the portfolio?" question. Prerequisites: market://{market_id}/status recommended for context. Next steps: get_position_detail, get_strategy_distribution. Caveats: paper-trading data only. Positions are not real money holdings. Disclaimer: Information only, not investment advice. Args: market_id: Market ID (crypto, kr_stock, us_stock) min_roi: Min ROI % filter (e.g., -5.0) max_roi: Max ROI % filter (e.g., 10.0) strategy: Strategy filter (e.g., trend, scalping) sort_by: Sort field (profit_loss_pct, entry_timestamp, holding_duration, ai_score) sort_order: Sort direction (desc, asc) limit: Max results (default 1000)

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• get_losing_positions

  OneQAZ Trading Intelligence

  Purpose: Losing paper positions (ROI < 0). Convenience wrapper around get_positions(max_roi=-0.01). Triggers (casual questions too): "what's underwater?", "지금 뭐가 물려 있어?", "show me the red ones", "any positions in trouble?", "얼마나 손실 중이야?". When to call: drawdown / risk review. Prerequisites: none. Next steps: get_position_detail, get_role_analysis. Caveats: paper-trading data only. Args: market_id: Market ID (crypto, kr_stock, us_stock; aliases coin/kr/us accepted) limit: Max results (default 20) Disclaimer: Information only, not investment advice.

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