"ICT Algorithmic Trading Strategy Development for TradingView" matching MCP tools:

• one_shot

  quantifyme

  End-to-end deploy: generate strategy → train → deploy live. One of `prompt` (free-form NL), `preset` (curated winning strategy), or `community_id` (copy a published community strategy) is required. If more than one is passed, precedence is community_id > preset > prompt. Args: prompt: Natural-language strategy description (e.g. "Buy when RSI < 30, sell > 70"). symbol: Currency pair to backtest on. One of: EURUSD, USDJPY, GBPUSD, USDCHF, USDCAD, AUDUSD, NZDUSD. Default EURUSD. timeframe: Candle granularity. One of: 1min, 5min, 15min, 1h. Default 15min. claude_model: Which Claude variant to use for code generation. "sonnet" (default — best quality, 1/day free) or "haiku" (faster, 3/day free). Ignored when `preset` is set (no generation needed). preset: Curated winning-strategy slug. Skips Claude generation entirely — deploys a pre-saved strategy known to backtest well on the chosen symbol. Available slugs: ema_cross_fast, momentum, scalper_stack, sma_only, trend_ema, volatility, bb_squeeze, all_mix, pivot_kid_ema. Not every slug exists for every symbol — call list_models afterwards to confirm what deployed. community_id: Copy-trade a published community strategy. Pass the `id` of an entry from `browse_community`. Loads that exact strategy code, skips Claude generation, then trains + deploys it. `symbol`/`timeframe` still apply to the backtest+deploy. webhook_url: Optional webhook to receive live signals. telegram_chat_id: Optional Telegram chat ID for signal delivery. Returns IMMEDIATELY (the deploy runs in the background so the live card can stream progress) with: - job_token (str): pass to get_deploy_result to fetch the final result. - poll_url (str): the card polls this for live progress; you can ignore it. - pending (bool): always true here — the deploy is still running. - symbol, timeframe (str). Call this EXACTLY ONCE per request. Pass the user's words as `prompt`; do not pre-pick presets/community strategies — the server routes (vague → a proven community strategy, specific rules → a fresh generation). NEXT STEP (always): call get_deploy_result(job_token) ONCE — it blocks until the deploy finishes and returns the out-of-sample stats + `stem` + `source`/`author` as TEXT so you can summarize. The live card already shows the chart, so you do NOT need get_model_chart. If source='community', tell the user it used a pre-existing strategy by @author and offer to generate a custom one.

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• global_indicator

  dynamic-feed

  A flagship development statistic from Our World in Data: the latest value for a country plus a short multi-year trend, with full source attribution. ONE source, MANY indicators (breadth) — CO2 per capita, population, fertility, urbanisation, GDP-per-capita (a development stat in PPP, NOT a market price), extreme poverty, R&D spend, Human Development Index, literacy, internet access, electricity access. Distinct from `global_macro` (World Bank): OWID adds the long-run development + climate set. `indicator` = a slug/alias from the curated allowlist (default "co2-emissions-per-capita"; aliases: co2, pop, gdp, hdi, literacy, internet, poverty, fertility, urban, rd) — call indicator="list" for the full menu. `country` = ISO-3 code (AUS, USA, CHN, GBR, IND, …); omit for the World aggregate. Source: Our World in Data (ourworldindata.org) — OWID's processing layer is CC BY 4.0, keyless; every response carries BOTH OWID's attribution AND each underlying producer's citation + licence. Only indicators whose underlying sources are cleared for commercial re-serving (CC BY / CC BY IGO / CC0 / public domain) are served — a fail-closed runtime gate refuses any non-redistributable indicator. Annual-ish statistics, not a live-telemetry feed. Every value is returned in an Ed25519-signed, provenance-stamped envelope (source and observation time) you can verify offline against /.well-known/keys, no account required.

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• switch_dannet_server

  dannet

  Switch between local and remote DanNet servers on the fly. This tool allows you to change the DanNet server endpoint during runtime without restarting the MCP server. Useful for switching between development (local) and production (remote) servers. Args: server: Server to switch to. Options: - "local": Use localhost:3456 (development server) - "remote": Use wordnet.dk (production server) - Custom URL: Any valid URL starting with http:// or https:// Returns: Dict with status information: - status: "success" or "error" - message: Description of the operation - previous_url: The URL that was previously active - current_url: The URL that is now active Example: # Switch to local development server result = switch_dannet_server("local") # Switch to production server result = switch_dannet_server("remote") # Switch to custom server result = switch_dannet_server("https://my-custom-dannet.example.com")

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• search_regulations

  Velvoite — EU Financial Regulatory Compliance

  Search the regulatory corpus using keyword / trigram matching. Uses PostgreSQL trigram similarity on document titles and summaries. Returns documents ranked by relevance with summaries and classification tags. Prefer list_documents with filters (regulation, entity_type, source) first. Only use this for free-text keyword search when structured filters aren't sufficient. Args: query: Search terms (e.g. 'strong customer authentication', 'ICT risk', 'AML reporting'). per_page: Number of results (default 20, max 100).

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• assess_opportunity

  PreFlyte — DeFi Financial Intelligence for AI Agents

  Assess the best DeFi opportunity for a given capital amount and strategy. This is the "cold start" tool — call it first to understand where your capital is viable before making any moves. One call gives you chain viability, ranked opportunities, gas impact, and an actionable recommendation. Args: api_key: Your PreFlyte API key (required). asset: Token symbol, e.g. "USDC", "WETH". action: "supply" or "borrow". position_size_usd: Capital amount in USD. strategy: One of "yield_farming", "active_trading", "idle_capital". chain: "ethereum", "arbitrum", or "any" (default: "any"). trades_per_day: For active_trading strategy only. Default 10. Returns: JSON with chain viability, ranked opportunities, gas analysis, break-even calculations, and an actionable recommendation.

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• find_strategy

  quantifyme

  Find an existing PROVEN strategy that matches a plain-English idea, so you can offer the user a choice — deploy the existing one, or generate a fresh custom one. Mirrors the quantifyme.ai landing experience: "Found <X> by @<author> (WR/PF) — Use it / Generate fresh". CALL THIS FIRST when a user describes a strategy idea. Then present the match (if any) and ASK which they want: • Use it → one_shot(community_id=<match.community_id>) — deploys the exact proven strategy (free, no generation). • Generate fresh → one_shot(prompt="<their description>") — Claude writes a brand-new custom strategy for them. If there's no match, just offer to generate fresh. Args: description: the user's strategy idea in plain English (e.g. "buy EURUSD 15min when RSI < 30, sell when RSI > 70"). symbol: optional pair to constrain the match (EURUSD, USDJPY, GBPUSD, USDCHF, USDCAD, AUDUSD, NZDUSD). timeframe: optional granularity to constrain the match (1min/5min/15min/1h). Returns: dict with: - match: the best existing strategy, or null. When present: {community_id, title, username, wr, pf, ret, n_trades, symbol, timeframe}. Pass community_id to one_shot to deploy it unchanged. - description: echoed back — pass as one_shot(prompt=...) to generate fresh. - suggestion: a ready-to-show sentence offering the user the choice.

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• get_strategy_schema

  Backtest360

  JSON Schema for the strategy document (condition_tree + indicators). Fetch this before composing a strategy by hand; the validate_strategy tool checks against the same rules.

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• arena_get_strategy_performance

  backtesting-arena

  Aggregated backtest performance for ONE specific (strategy, asset, interval) combination. Returns run_count, avg_cagr, avg_win_rate, avg_drawdown, effective_years, and vs_buy_hold comparison (beats_buy_hold, cagr_delta). For multi-strategy overview use arena_get_strategy_insights. Use this to answer 'How does strategy X perform on asset Y?'. [Free tier]

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• cc.central_signal

  Central Command

  Call cc.central_signal — Unified signal ingestion endpoint that normalizes symbols from any exchange format (Binance, Bybit, TradingView) to executable format and routes to execution. Purpose: Unified signal ingestion endpoint that normalizes symbols from any exchange format (Binance, Bybit, TradingView) to executable format and routes to execution. Behavior: DESTRUCTIVE. Normalizes the signal and routes toward trade execution for the authenticated account. Can open/close positions. Auth: X-Api-Key required (and linked exchange credentials for execution actions). Cost: $0.01 USDC per successful call (x402 Base USDC pay-per-use or prepaid X-Api-Key balance). Linked Connect keys are free. This is billing, not a side effect. Rate limit: 30/min (per API key). Tier: premium. Returns: Signal confirmation with execution status, order ID, fill price, and routing metadata. Guidelines: Use for research / signal context. Pair with cc.agent_strategy (paper) before any live order. Do not invent fills from this data alone. Tags: signals, execution, routing, tradingview, webhook, automation.

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• get_hypothesis

  VARRD — Statistically Validated Trading Edges + AI Research Engine

  Get full detail for a specific hypothesis/strategy. Returns formula, entry/exit rules, direction, performance metrics (win rate, Sharpe, profit factor, max drawdown), version history, and trade levels. Everything an agent needs to understand and act on a strategy.

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• get_playbook_status

  RiskState — Crypto Risk Engine

  Trading Playbook Engine status: the registry of rule-based trade setups (playbooks) for BTC and ETH and which ones are firing right now, with structure-gate verdicts, cooldown state and why non-firing setups do not match (failed predicates with live market readings). Strategy-level only — no prices, sizes or portfolio data. Use for questions about active trade setups or what the playbooks are watching.

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• compare_strategies

  Noon Barbari Backtesting

  Head-to-head comparison of two strategy templates from real monthly engine runs across ~50 coins: per-coin win count, median out-of-sample Sharpe, survival counts, median return and drawdown. Use strategy names from list_strategies (e.g. 'super_trend', 'ema_crossover').

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• cc.openclaw_chat

  Central Command

  Call cc.openclaw_chat — Autonomous AI agent specialized in strategy development, backtesting, and continuous market monitoring. Uses indicator libraries, pattern recognition, and instrument specifications. Purpose: Autonomous AI agent specialized in strategy development, backtesting, and continuous market monitoring. Uses indicator libraries, pattern recognition, and instrument specifications. Behavior: conversational AI that CAN place/cancel orders and manage positions when the linked account allows it. Treat as potentially destructive. Confirm intent before asking it to trade live. Auth: X-Api-Key required (and linked exchange credentials for execution actions). Cost: $0.025 USDC per successful call (x402 Base USDC pay-per-use or prepaid X-Api-Key balance). Linked Connect keys are free. This is billing, not a side effect. Rate limit: 10/min (per API key). Tier: enterprise. Returns: Structured AI analysis with computed indicators, detected patterns, strategy recommendations, and task management for autonomous execution. Guidelines: Prefer paper/simulation paths. For live money require explicit human confirmation (confirm_live / action=execute). Report real HTTP errors; never invent proxy failures. Tags: ai, strategy, autonomous, backtesting, patterns, indicators.

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• donate

  Blueprint Agentic Staking (Solentic)

  Build an unsigned SOL transfer to support Blueprint development. Blueprint provides free staking infrastructure for AI agents — donations help sustain enterprise hardware and development. Same zero-custody pattern: unsigned transaction returned, you sign client-side. Suggested amounts: 0.01 SOL (thank you), 0.1 SOL (generous), 1 SOL (patron).

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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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• development_appraisal

  property-finance-mcp

  Run a UK property development scheme viability appraisal. Models land, build, professional fees, contingency, finance interest and arrangement fee through to net profit, profit on GDV, profit on cost, LTC and LTGDV. Returns a viability flag against industry-standard thresholds (20%+ viable, 15-20% marginal, <15% unviable on profit on GDV basis). Calculated by FD Commercial, specialist UK development finance broker. Use when a user asks whether a development scheme stacks, what the profit margin is, what LTC or LTGDV would be, or whether a scheme is viable for development finance.

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• bounty_submit

  invinoveritas

  Submit a trading-edge idea to the governed edge-idea bounty. You are paid a FLAT sats bounty for the IDEA if it survives the same backtest gate (Monte-Carlo permutation p-value + Deflated Sharpe) our own live trading bot is held to — no capital is pooled, you keep your funds, we buy the idea. Tiers auto-detected from `spec`: parameter (a search grid on an existing strategy family), code (a novel signal function — run only in a hardened, network-off Docker sandbox), or concept (a free-text idea). A code-tier signal_code must define generate_signals(candles).

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• list_goals

  Un Sdg

  List the 17 UN Sustainable Development Goals (code, title, description). Optionally drill into one goal to get its targets and indicators.

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• arena_get_strategy_insights

  backtesting-arena

  Aggregated backtest performance per (strategy × interval) cell. If `strategy` AND `interval` provided, returns detail with per-asset breakdown + param variants. Otherwise returns the full matrix (Top-10 cells for Free tier; full for Pro+). [Free Top-10 / Pro+ full]

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• arena_get_strategy_performance_by_regime

  backtesting-arena

  Historical backtest performance for ONE (strategy, asset, interval) combination SPLIT BY macro market regime (sweet_spot / late_cycle_warning / crisis / recovery — classified at each trade's entry date), PLUS a recommendation for the CURRENT live regime. Answers the killer question 'Should I trade this strategy NOW?'. Each regime bucket returns trades, win_rate, avg_pnl_pct, reward_risk_ratio (per-trade mean/stddev, NOT annualized Sharpe), share_of_time_pct and a rating. [Free tier]

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