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605,840 tools. Updated 2026-09-24 05:25

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

  • Get a debt paydown analysis with payoff projections. Call with NO arguments to get the user's SAVED plan — their chosen strategy plus their saved extra monthly payment, the exact numbers the Debt Paydown page shows them. When the user asks "when will I be debt-free?" / "what's my payoff date?", use the no-argument call and report the returned `debt_free_date`, `projection`, and `strategy` VERBATIM — never re-derive a date from the month count and never substitute a different strategy. Only pass `strategy`/`extra_monthly` for explicit what-if questions ("what if I paid $200 extra?"). Args: extra_monthly: Extra monthly payment beyond minimums. Omit to use the user's saved extra payment (their plan). strategy: Payoff strategy - highest_rate, snowball, variable_snowball, minimum_payments, highest_balance, highest_payment, cashflow_index, npv, max_interest_savings. Omit to use the user's saved plan strategy. respect_goal_priorities: When True (default), active debt-payoff goals override strategy ordering for the primary projection. Pass False to see what the chosen strategy would do without goal interference. The strategies_comparison table always shows pure strategy ordering regardless of this flag. For "what should I pay this month?" / "which debt gets my extra?", read `this_month`: `this_month.target` is the debt the plan attacks first (`target_basis`: extra_this_month, or first_rollover when no extra is set and freed-up payments start rolling to it in `first_extra_month`). Each row has payment (what to send = minimum_payment + extra), minimum_payment (the account's stated minimum), and plan_minimum_payment / plan_payment (the projection's amortized figures, which can differ by a few dollars). Quote payment and minimum_payment as-is. Returns: Debt payoff timeline (incl. debt_free_date — quote it as-is), this_month (per-debt payments + the target debt), interest savings, strategy comparison, and is_user_saved_plan (True when the projection is the user's own saved plan).
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  • How did this exact strategy, asset and interval perform? Aggregated backtest performance for ONE specific (strategy, asset, interval) combination. Returns run_count, avg_cagr, avg_win_rate, avg_drawdown, effective_years, vs_buy_hold comparison (beats_buy_hold, cagr_delta) and an `evidence` block declaring the gate machine-readably (gate_applies_to: stats.run_count, threshold 5 runs, benchmark value, aggregation data window). 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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  • Which of these strategies performed best on the same data? Run 2–5 strategies against the SAME pair, interval and date range and return per-strategy metrics plus a comparison summary (best by CAGR, best by win-rate, worst by drawdown). Use this when the user asks which of several strategies fits a market — it holds the pair, interval and requested date range fixed, which a series of separate arena_run_backtest calls does not guarantee. What it does NOT equalize is the EVALUATION window: a strategy with a long warmup starts trading later, so compare actual_date_from across the runs and check result.benchmark before ranking by CAGR. For one strategy across many pairs use arena_run_universe_backtest instead. Caveat worth passing on: comparing N strategies and reporting the winner IS multiple testing — the winner’s edge is upward-biased. arena_get_robustness_field puts a counted N on that. Sequential, expect 10–50s. Per-day quota: Pro=20, Power=200. [API Pro tier]
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  • Approve a StrategySuggestion, optionally creating the suggested Strategy. Closes the PROPOSE loop for MCP-only agents: wraps the same approve-and-create service logic as the REST ``StrategySuggestionViewSet.approve`` action instead of a manual ``suggested_config`` round-trip through the strategy create tools, which silently drops the suggestion linkage (``StrategySuggestion.created_strategy`` / hive DecisionRecord.suggestion FK provenance). ``wallet_address`` is the caller's own wallet (recorded as ``approved_by_wallet``); when ``agent_wallet_id`` also resolves to a wallet ``wallet_address`` controls, the suggested Strategy is created through the same executor dry-run gate as every other create path. ``config_overrides`` merges over ``suggested_config`` (e.g. a real ``usd_per_buy``). A wallet without a Turnkey signer still gets the strategy -- paper trade, unsigned tx per tick. Informational rationale only (rules 5-8); the created strategy still runs only through the existing engine gates. Workflow: DECIDE -> EXECUTE step -- the MCP-only closing move for get_strategy_suggestions; pair with backtest_strategy + get_risk_assessment first for the same guardrails any other create path gets.
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  • Run a sandbox backtest of strategy code without persisting anything. This is the fastest way to test a strategy. The code is run through static checks and a full backtest on historical data, but no Strategy or StrategyVersion rows are created. Use this for rapid iteration. Args: code: Python source code implementing the Strategy contract. Must define a METADATA dict and a class extending Strategy with an on_bar(ctx) -> Signal method. See CREATOR_API.md. domain: Trading domain (e.g. "eth_usdc", "btc_usdc", "sol_usdc"). symbol: Price symbol for historical data (e.g. "ETHUSDT"). user_id: Identifier for trial tracking (used for DSR correction). Returns JSON with: success, metrics (sharpe, sortino, win_rate, total_trades, return_bps, max_drawdown, regime_breakdown, exit_reason_breakdown), or error details if validation failed.
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  • Log a completed or skipped recovery/mindfulness session. Use when the user says they did (or skipped) a breathing exercise, meditation, cold plunge, sauna, stretching, or any recovery practice. Also use for one-off standalone sessions not linked to a recurring strategy. INFER — do not ask: - date: default to today - category: infer from the practice name - strategy_name: use the strategy name if linked, or the user's description - duration_minutes: infer if mentioned (omit for skipped sessions) - quality: only include if the user rates it (1-5 scale) - skipped: true when the user says they skipped, missed, or didn't do a session; false (default) for completed sessions PREFERRED WORKFLOW: call list_recovery_strategies first to link the session to an active strategy for adherence tracking. If no matching strategy exists, log as standalone.
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Matching MCP Connectors

  • Live crypto trend signals, cross-asset ranking, and on-demand backtesting for BTC/ETH/SOL/XRP/ADA, backed by a transparent, independently-verifiable systematic methodology — every number backtestable yourself, not a black box. x402 USDC on Base & Solana via Coinbase CDP facilitator, $0.01-$0.28/call. No API keys.

  • Live crypto trend signals, ranking, and backtesting for BTC/ETH/SOL/XRP/ADA. x402 pay-per-call.

  • Search the Klever VM knowledge base for smart contract development context. Returns structured JSON with matching entries, scores, and pagination. Use this for precise filtering by type or tags; use search_documentation for human-readable "how do I..." answers.
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  • 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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  • 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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  • Which strategy and interval combinations actually performed? Aggregated backtest performance per (strategy × interval) cell. If `strategy` AND `interval` provided, returns detail with per-asset breakdown + param variants. Otherwise returns the matrix. Free tier is limited to the same strategies that are free in the backtester itself (rsi_sma, golden_cross, rsi_ob_os, bnh_fixed, dca_reference); the response then carries `plan_capped: true` plus `plan_cap_note`, so a short matrix is never mistaken for a thin database. Detail mode on a Pro-only strategy returns 403 rather than a silently empty answer. API Pro and Power receive every cell. [Free: 5 strategies / Pro+: full]
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  • L3 Empathy Response Strategy: converts text into a deterministic response strategy (approach, tone temperature, pacing, focus points, avoid-list) for AI companions and conversational agents. Deterministic table lookup, no LLM, ~20ms; privacy-first. Not a medical or therapeutic tool.
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  • Deactivate and unlink an algorithm from a trading instance, stopping that linked strategy without deleting the saved algorithm. Use this before delete_algo; it is reversible with activate_algo, but inspect open positions first because deactivation does not automatically flatten broker exposure.
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  • Call cc.external_signal — Public-facing webhook endpoint for TradingView alerts, custom bots, and third-party signal providers. Normalizes and forwards to execution. Purpose: Public-facing webhook endpoint for TradingView alerts, custom bots, and third-party signal providers. Normalizes and forwards 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: $0.005 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: 60/min (per API key). Tier: standard. Returns: Proxied execution response: signal received, validated, normalized, and forwarded to trade engine. 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: webhook, tradingview, alerts, automation, signals.
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  • Call cc.external_signal — Public-facing webhook endpoint for TradingView alerts, custom bots, and third-party signal providers. Normalizes and forwards to execution. Purpose: Public-facing webhook endpoint for TradingView alerts, custom bots, and third-party signal providers. Normalizes and forwards 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: $0.005 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: 60/min (per API key). Tier: standard. Returns: Proxied execution response: signal received, validated, normalized, and forwarded to trade engine. 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: webhook, tradingview, alerts, automation, signals.
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  • Get the versioning strategy configured for an API specification, including version aliases. Use this to read the strategy; to change it use set_versioning_strategy. Requires project context.
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  • Detect the current market regime to inform trading strategy. Use this tool alongside get_risk_index before making trading decisions. Returns one of four regimes: BULL (S&P 500 above 200-day MA, VIX below 20), BEAR (S&P 500 below 200-day MA), SIDEWAYS (range-bound, low directional conviction), CRISIS (extreme volatility, VIX above 30). Also returns: confidence percentage, S&P 500 price vs 200-day MA, current VIX level, and regime duration. Updated every 30 minutes. FREE — no API key required.
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  • Get a random Disrupt strategy. Use when stuck in safe patterns, avoiding risk, or when work feels too polished or predictable. Best for injecting energy and unpredictability. Use this when: break patterns, embrace chaos, make destructive moves, honor mistakes. Returns a labeled strategy card to help shift your perspective and break through blocks.
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  • Search OPEN PHILANTHROPY JOBS at grantmaking foundations. Surfaces roles involved in giving away money, running philanthropic programs, or executive leadership of philanthropic work. Backed by a weekly scrape of ~50K funder careers pages + GPT-5.4-mini classification against an 8-category taxonomy. Categories (use the `category` param to filter): - grantmaking: Program officers, grants managers, RFP reviewers - program_leadership: VP Programs, Chief Program Officer, Program Director (cause-area) - executive_leadership: CEO, President, Executive Director at a foundation or community foundation - philanthropy_operations: Foundation finance/HR/IT/COO - program_support: Program associates, M&E officers, learning officers, program coordinators - development_for_grantmaking: Major gifts officers and development roles at community foundations and other regranting entities (NOT university or hospital development for the parent's operations) - philanthropy_communications: Foundation comms staff - philanthropy_strategy: Chief Strategy Officer, impact officer, equity & inclusion at a foundation What's excluded by design: clinical/medical, retail, academic teaching, university advancement for the university itself, hospital fundraising for hospital ops, construction/facilities.
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  • Get full detail for a specific LP strategy by ID — includes APY per range width (narrower range = higher APY but more rebalancing cost/risk), pool info, and configuration. Use read_strategy_list to discover strategy IDs. All APY values are decimal fractions (1.0 = 100%, 0.05 = 5%).
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  • Get the runtime and development dependencies for a specific version of a Ruby gem. Returns each dependency with its version requirement string. Omit version to get the latest.
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  • Search the Pinnacle Ask child-development knowledge corpus (pinnacleblooms.org/ask) — real parent questions with clinically grounded, non-diagnostic answers covering speech, motor, social, cognitive, sensory, feeding and behavioural development from birth to 18 years. Returns ranked results with ids; pass a result id to `fetch` for the full answer. Optionally filter by child age in months and/or developmental domain.
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