dMoERA Creator

io.github.CacheCarti由 GitHub 帳號 CacheCarti 發布v1.0.0更新於 Oct 24, 2026

Build, backtest, and deploy crypto trading strategies via MCP with 7-stage validation.

已驗證Streamable HTTP可網頁執行金融開發者工具資料與分析

概覽

AI 產生的概覽

dMoERA Creator 讓 AI 助理在 dMoERA 平台上撰寫、回測並提交加密貨幣交易策略,並管理個人對沖基金。

可以做什麼
  • 查詢交易領域、資料來源、市場狀態、即時價格與依績效排序的機器人
  • 在沙盒中回測策略程式碼,提交後執行 7 階段驗證流程,並檢視策略報告
  • 瀏覽市場機器人、開源機器人、錦標賽與排行榜
  • 建立並設定個人對沖基金:名單、權重、風險上限、啟用與關閉
  • 追蹤基金持倉、成交、損益、分析與不可變報告卡
  • 設定基金對外的經理人設與陣型範本
適用情境
適合想讓助理依歷史資料反覆調整 Python 加密交易策略並部署,或在對話中組成並監控自己機器人組合的情境。
執行需求
可連線 dmoera.xyz/mcp 的遠端 Streamable HTTP 端點,或本機 Python 3.11+ 環境(需 mcp 套件與 DMOERA_API_URL)。個人存取權杖(DMOERA_API_KEY)對公開行情資料為選用,但回測、提交、分支、下架策略以及所有基金工具都需要它。
安裝前請注意
基金工具會動用真實資金:建立基金會從錢包現金扣款,啟用 Manager Mode 會部署資金,關閉基金無法復原。替換機器人會產生摩擦成本。API 金鑰可寫入你的策略與基金,務必保密且不要提交到程式庫。策略程式碼會傳送到遠端 dMoERA 後端進行驗證與執行。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 dMoERA Creator,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.CacheCarti%2Fdmoera-creator/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "dmoera-creator": {
      "type": "http",
      "url": "https://dmoera.xyz/mcp"
    }
  }
}

README

dMoERA Creator Studio — MCP Server

[Smithery]

[dMoERA MCP Demo]

Build, backtest, and deploy crypto trading strategies using any MCP-compatible AI agent (Claude, Cursor, Windsurf, Devin, Copilot, etc.).

What it does

The dMoERA MCP server exposes the dMoERA Creator API as Model Context Protocol tools. Your AI agent can:

  • Discover trading domains, data feeds, and market regimes
  • Inspect existing bots and their live performance metrics
  • Backtest strategy code in a sandboxed environment
  • Submit strategies for full 7-stage validation and live deployment
  • Manage personal hedge funds — create funds, add your own bots, activate Manager Mode
  • Monitor tournament status, Tag Team leaderboards, and Vault allocation
  • Track fund positions, trades, P&L, analytics, and immutable report cards

This is a thin API client — it talks to a running dMoERA backend via HTTP. No internal dMoERA code is required.

Installation

Prerequisites

  • Python 3.11+
  • The mcp Python package (pip install mcp)
  • A running dMoERA backend (or connect to the public instance)

Setup

bash
git clone https://github.com/CacheCarti/dmoera-mcp.gitcd dmoera-mcppip install -r requirements.txt

MCP Configuration

Add this standard MCP configuration to Claude Desktop, Cursor, Windsurf, or another MCP client:

json
{  "mcpServers": {    "dmoera-creator": {      "command": "python",      "args": ["/absolute/path/to/dmoera-mcp/mcp_creator_server.py"],      "env": {        "DMOERA_API_URL": "https://dmoera.xyz",        "DMOERA_API_KEY": "your_optional_personal_access_token"      }    }  }}

The API key is optional for public market data and discovery tools. Create a Personal Access Token at dmoera.xyz under Settings → API Keys to backtest, submit, fork, open-source, or delist strategies. Never commit your token.

Remote clients can connect through the Streamable HTTP endpoint:

text
https://dmoera.xyz/mcp

Tools (44 total)

Discovery & Market Data

ToolDescriptionAuth Required
list_domainsList all available trading domains (ETH, BTC, SOL — spot and scalp)No
list_botsList trading bots ranked by performance, optionally filtered by domainNo
get_bot_profileGet detailed profile and performance stats for a specific botNo
get_feature_catalogList all data feeds available to strategies via ctx.featuresNo
get_market_regimeGet current market regime classificationNo
get_current_pricesGet current live prices for all tracked symbolsNo

Strategy Development

ToolDescriptionAuth Required
sandbox_backtestBacktest strategy code in a sandboxed environmentYes
submit_strategySubmit a strategy for full validation and live deploymentYes
list_strategiesList all strategies created by a userYes
get_strategy_reportGet a detailed report card for a strategyNo

Marketplace & Tournaments

ToolDescriptionAuth Required
get_marketplace_botsList bots published to the marketplaceNo
get_tournament_statusGet current tournament round status and leaderboardNo

Fund Management (personal funds — own bots only)

Personal funds can only contain the authenticated user's own bots. Use list_my_bots to see eligible strategies.

ToolDescriptionAuth Required
list_fundsList your funds (active + closed)Yes
get_fundFund details including rosterYes
get_active_fundCurrently active Manager Mode fundYes
create_fundCreate a personal hedge fundYes
add_bot_to_fundAdd your own bot to a fund's rosterYes
remove_bot_from_fundRemove a bot from the rosterYes
swap_bot_in_fundSwap one bot for another (friction cost applies)Yes
update_fund_weightsUpdate allocation weights for roster botsYes
update_fund_capsUpdate risk caps (max per bot, per domain, regime veto)Yes
activate_fundActivate Manager Mode — starts the personal routerYes
deactivate_fundDeactivate Manager Mode — return to main routerYes
close_fundPermanently close a fund (capital returned to wallet)Yes
estimate_swap_costEstimate friction cost (bps) before swapping botsYes
list_my_botsYour own bots eligible for a personal fund rosterYes
list_open_source_botsBrowse the broader open-source bot ecosystemNo
get_fund_positionsOpen positions for a fund's roster botsYes
get_fund_tradesClosed trade history for a fund's roster botsYes
get_fund_performanceP&L time-series snapshots for a fundYes
get_fund_live_pnlReal-time cumulative PnL chart from closed positionsYes
get_fund_analyticsDashboard analytics: allocation, per-bot performance, riskYes
run_fund_historical_testSimulate a roster against historical data (rate limited)Yes
generate_fund_report_cardGenerate an immutable report card for a fundYes
get_fund_report_cardGet the latest report card for a fundYes

Tag Team (daily paper trading competition)

ToolDescriptionAuth Required
tag_team_infoSession info, open positions, bot status, rankYes
tag_team_templatesCo-Pilot templates (momentum, scalper, etc.)No
tag_team_leaderboardDaily leaderboard (optional date filter)Yes
tag_team_weeklyWeekly championship standingsYes
tag_team_historyPast sessions with scoresYes
tag_team_tierTier progression (Rookie → Master)Yes
tag_team_badgesEarned badges (Daily Champion, Bot Whisperer, etc.)Yes

Vault (regime-aware allocation)

ToolDescriptionAuth Required
get_vault_statusCurrent regime, allocation weights, sleeve holdingsYes
get_vault_historyRegime switch timelineYes

Resources

  • creator-api://docs — Full strategy contract documentation
  • creator-api://strategy-template — Copy-pasteable strategy template

Example Usage

Ask your AI agent:

"List all trading domains on dMoERA, then backtest a simple RSI mean-reversion strategy for ETH/USDC."

The agent will call list_domains, inspect the available markets, then call sandbox_backtest with strategy code it generates. You can iterate:

"The Sharpe is too low. Try adding a volatility filter — only trade when ATR is above its 20-period average."

"Submit this strategy to the ETH/USDC domain."

The agent calls submit_strategy, which runs the full 7-stage validation pipeline. If it passes, the strategy enters the live Arena and competes for tournament payouts.

Hedge Fund Management

"Create a personal hedge fund called 'Alpha Seeker' with a standard risk preset. Then list my eligible bots."

The agent calls create_fund, then list_my_bots to show which of your strategies can be added to the roster.

"Add my momentum ETH bot with 30% weight and my scalper BTC bot with 20% weight, then activate the fund."

The agent calls add_bot_to_fund twice, update_fund_weights, then activate_fund to start the personal router.

"How's the fund doing? Show me the analytics and latest report card."

The agent calls get_fund_analytics and get_fund_report_card.

Strategy Contract

Strategies subclass Strategy and implement on_bar(self, ctx) -> Signal. See the creator-api://docs resource for the full contract.

python
class MyStrategy(Strategy):    METADATA = {        "name": "SMA Crossover",        "domain": "eth_usdc",        "declared_sl_bps": 150.0,        "declared_tp_bps": 300.0,        "declared_hold_seconds": 3600,        "warmup_bars": 20,        "required_features": [],    }
    def on_bar(self, ctx):        closes = ctx.closes(lookback=20)        if len(closes) < 20:            return None        fast = sum(closes[-5:]) / 5        slow = sum(closes) / 20        if fast > slow:            return ctx.signal(                direction=SignalDirection.LONG,                confidence=0.7,                stop_loss_bps=150.0,                take_profit_bps=300.0,                horizon_seconds=3600,            )        return None

Hedge Fund System

Personal hedge funds (Manager Mode) let you build a portfolio of your own bots:

  1. Create a fund with a risk preset (prudent, standard, opportunistic, unrestricted)
  2. Add your own bots to the roster with allocation weights
  3. Set risk caps — max allocation per bot, per domain, regime veto
  4. Activate Manager Mode to deploy capital across the roster
  5. Monitor PnL, swap bots as needed, adjust weights
  6. Generate immutable report cards for track record
  7. Close the fund to return all capital to your wallet

The personal router replaces the main platform router while Manager Mode is active, giving you full control over which bots trade and how much capital they get. Personal funds can never contain another user's bots.

Tag Team System

Tag Team is a standalone daily paper-trading competition, separate from the main router and tournaments:

  • Start: Pick a Co-Pilot template (momentum, scalper, etc.) → get $10,000 paper capital
  • Capital split: 70% human ($7,000), 30% Co-Pilot bot ($3,000)
  • Manual trades: 20 max per day, leverage 1-20x
  • Bot deploy: After 3 closed manual trades, deploy the Co-Pilot
  • Scoring: Need 5+ human trades AND 5+ bot trades to qualify
  • End: At UTC midnight, all open positions close at market price
  • Next day: Fresh $10k, but bot params carry over (trained settings persist)

Tiers: Rookie (0) → Apprentice (10) → Trader (50) → Veteran (150) → Expert (500) → Master (1000+), based on total trades across all sessions.

Tournament System

Bots compete in 3-day tournament rounds. Scoring is based on the bot's own performance:

  • 50% risk-adjusted (rolling Sharpe ratio)
  • 30% total return (log-scaled bps)
  • 20% consistency (win rate × trade volume)

Top 3 per domain win USDT from the reward pool. No user following needed to qualify — your bot competes on its own metrics.

Links

License

MIT

來源:README.md,提交 2d90ba6

工具

59

list_domains

List all available trading domains on dMoERA. Domains define what asset pair a strategy trades, what time horizon it uses (scalp=5m, swing=1h, crisis=2m), and what data is available. Strategies must declare which domain they belong to. Returns a JSON array of domain objects with: key, name, type, base_asset, quote_asset, grading_seconds, and feed_symbols.

無需輸入參數。

list_bots

List trading bots ranked by performance. Args: domain: Filter by domain key (e.g. "eth_usdc", "btc_usdc", "sol_usdc"). If omitted, returns top bots across all domains. limit: Maximum number of bots to return (default 20, max 100). Returns JSON array of bots with: bot_id, domain, strategy_name, sharpe, win_rate, total_trades, return_bps, and validation_score.

輸入參數limitdomain

get_bot_profile

Get detailed profile and performance stats for a specific bot. Args: bot_id: The bot identifier (e.g. "Eth_Full_Ensemble"). Returns JSON with: bot_id, domain, strategy type, full performance metrics (Sharpe, Sortino, Calmar, profit factor, regime breakdown), current position if any, and recent trade history.

輸入參數bot_id必填

get_feature_catalog

List all data feeds available to strategies via ctx.features. Features are external data that strategies can read during on_bar(). Each feature has a status: "live" (available now, requirable) or "planned" (roadmap, not yet available). Only live features can be used in required_features. Returns JSON array of features with: key, label, description, unit, example, cadence, source, status, and backtest_mode.

無需輸入參數。

get_market_regime

Get current market regime classification. Returns the aggregate regime (e.g. "bull_calm", "bear_volatile"), per-symbol regimes, crisis score, and the derivatives data driving the classification (funding rates, open interest, long/short ratios, taker buy/sell ratios). Regime determines which trade directions are allowed: - bull_* → longs only - bear_* → shorts only - neutral_* → both longs and shorts - crisis/meltdown → no new positions

無需輸入參數。

get_current_prices

Get current live prices for all tracked symbols. Returns JSON with symbol → {price, bid, ask, source, change_24h_pct, volume_24h} for ETHUSDT, BTCUSDT, SOLUSDT from Binance/Coinbase/Kraken.

無需輸入參數。

sandbox_backtest

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.

輸入參數code必填domainsymboluser_id

submit_strategy

Submit a strategy for full validation and live deployment. Runs the complete 7-stage validation pipeline: 1. static_check — code safety (banned imports, syntax) 2. in_sample — sanity check on training data 3. out_of_sample — test on unseen data (70/30 split) 4. walk_forward — rolling window validation 5. randomized_start — different random start points 6. perturbation — market stress test 7. holdout — server-side reserved data (pass/fail only) If all stages pass, the strategy is registered for isolated live paper trading with status="incubating". Promotion to "live" requires a proven track record. Args: name: Human-readable strategy name (e.g. "ETH Momentum v2"). domain: Trading domain key (e.g. "eth_usdc"). code: Python source code implementing the Strategy contract. user_id: The creator's user ID. symbol: Price symbol for historical data. Returns JSON with: success, strategy_id, bot_id, validation results per stage, or error details.

輸入參數code必填name必填domain必填symboluser_id必填

list_strategies

List all strategies created by a user. Args: user_id: The creator's user ID. Returns JSON array of strategies with: id, bot_id, name, domain, status, declared_sl_bps, declared_tp_bps, and created_at.

輸入參數user_id必填

get_strategy_report

Get a detailed report card for a strategy. Includes validation run results for all 7 stages, performance metrics, and the integrity block (code hash, AST hash, parameter fingerprint). Args: strategy_id: The strategy's database ID. Returns JSON with: strategy details, latest validation runs, metrics.

輸入參數strategy_id必填

get_marketplace_bots

List bots published to the marketplace. Args: domain: Filter by domain (e.g. "eth_usdc"). Omit for all domains. sort: Sort order — "rating", "return", "subscribers", or "newest". limit: Max results (default 20, max 100). Returns JSON array of marketplace listings with: listing_id, bot_id, title, description, domain, creator, monthly_price_usd, cached stats (win_rate, return_bps, sharpe), subscriber_count, and avg_rating.

輸入參數sortlimitdomain

get_tournament_status

Get current tournament round status and leaderboard. Tournaments run every 3 days. Top 3 bots per domain win prizes from the reward pool. Scoring is weighted: 50% risk-adjusted return, 30% total PnL, 20% consistency. Returns JSON with: current round info (round_id, start/end time, reward_pool_usd, total_participants), and leaderboard entries.

無需輸入參數。

list_funds

List all hedge funds for the authenticated user (active + closed). Returns a JSON array of fund objects with: id, fund_name, is_active, inception_date, initial_capital, current_aum, router_preset, aggression_mode, total_pnl_usd, total_pnl_bps, and roster summary.

無需輸入參數。

get_fund

Get detailed info for a specific hedge fund, including its roster. Args: fund_id: The fund's ID. Returns a JSON object with fund details and active roster entries (bot_id, bot_name, weight, domain, current_pnl).

輸入參數fund_id必填

get_active_fund

Get the authenticated user's currently active (Manager Mode) fund. Returns the active fund object or null if Manager Mode is not active.

無需輸入參數。

set_fund_lineup

Replace your fund's live lineup in one call. roster: [{"bot_id": "dir_long_btc", "weight_pct": 60}, {"bot_id": "...", "weight_pct": 25}] Weights are % of the fund; anything under 100 stays in cash. Bots that stay keep their positions, removed bots are closed at market, new bots open on their next signal (Always Long/Short bots open right away). The change and your rationale go into the fund's public history.

輸入參數roster必填fund_id必填rationale

create_fund

Create a new personal hedge fund for the authenticated user. The fund starts inactive — call activate_fund to start Manager Mode. Initial capital is taken from the user's wallet_cash at creation time. Personal funds can ONLY contain the user's own bots — use list_my_bots to see eligible strategies. Args: fund_name: Display name for the fund. router_preset: Risk profile — one of "prudent", "standard", "opportunistic", "unrestricted". aggression_mode: "weights" (default — the fund follows your weights exactly; leftover % stays in cash) or "router" (opt-in Kelly sizing; needs bots with a trade history). philosophy: Optional text describing the fund's investment thesis (max 2000 chars). fund_type: "personal" (your bots + live/open-source platform bots + directional bots; default), "standard" (platform bots), or "open_source" (open-source bots only). Returns the created fund object.

輸入參數fund_namefund_typephilosophyrouter_presetaggression_mode

add_bot_to_fund

Add a bot to a fund's roster. Personal funds can only contain the authenticated user's OWN bots. Use list_my_bots to see eligible strategies. Args: fund_id: The fund's ID. bot_id: The bot to add (e.g. "momentum_eth_v3"). bot_domain: The bot's domain (e.g. "eth_usdc", "btc_usdc"). weight: Initial allocation weight in percent (default 20.0). rationale: Why you're adding it — published in the fund's manager log. Returns the updated roster entry.

輸入參數bot_id必填weightfund_id必填rationalebot_domain必填

remove_bot_from_fund

Remove a bot from a fund's roster (triggers wind-down of its positions). Args: fund_id: The fund's ID. bot_id: The bot to remove. reason: Optional reason for removal. Returns success or error.

輸入參數bot_id必填reasonfund_id必填

swap_bot_in_fund

Swap one bot for another in a fund's roster. Closes the old bot's positions and opens new ones for the replacement. Incurs friction cost — use estimate_swap_cost first. Args: fund_id: The fund's ID. old_bot_id: The bot to remove. new_bot_id: The bot to add in its place. new_bot_domain: The new bot's domain (e.g. "eth_usdc"). weight: Allocation weight for the new bot (defaults to old bot's weight). reason: Optional reason for the swap. Returns the updated roster entry and friction estimate.

輸入參數reasonweightfund_id必填new_bot_id必填old_bot_id必填new_bot_domain必填

update_fund_weights

Update allocation weights for bots in a fund's roster. Args: fund_id: The fund's ID. weights: A dict mapping bot_id to new weight percentage (e.g. {"momentum_eth_v3": 15.0, "scalper_btc_v2": 20.0}). Returns success or error.

輸入參數fund_id必填weights必填

update_fund_caps

Update a fund's risk caps and settings. Args: fund_id: The fund's ID. max_per_bot_pct: Max allocation per single bot (e.g. 40.0 = 40%). max_per_domain_pct: Max allocation per domain (e.g. 60.0 = 60%). regime_veto_enabled: Whether the regime detector can veto trades. Only provided fields are updated; others remain unchanged. Returns success or error.

輸入參數fund_id必填max_per_bot_pctmax_per_domain_pctregime_veto_enabled

activate_fund

Activate Manager Mode for a fund — starts the personal router. This deploys capital across the fund's roster bots according to their weights and the fund's risk caps. The main platform router is paused while Manager Mode is active. Args: fund_id: The fund's ID. Returns success or error.

輸入參數fund_id必填

deactivate_fund

Deactivate Manager Mode — returns to the main platform router. Closes all roster bot positions and returns capital to the wallet. Args: fund_id: The fund's ID. Returns success or error.

輸入參數fund_id必填

close_fund

Permanently close a hedge fund. Returns all capital to the wallet. This is irreversible. The fund's performance record is preserved for reporting and copy-trader settlement. Args: fund_id: The fund's ID. Returns success or error.

輸入參數fund_id必填

estimate_swap_cost

Estimate the friction cost (in bps) of swapping a bot in a fund. Use this before calling swap_bot_in_fund to understand the cost of winding down the old bot's positions and opening new ones. Args: fund_id: The fund's ID. old_bot_id: The bot being considered for removal. new_bot_id: The replacement bot. new_bot_domain: The replacement bot's domain. Returns the estimated friction in bps of fund AUM.

輸入參數fund_id必填new_bot_id必填old_bot_id必填new_bot_domain必填

list_open_source_bots

Browse open-source bots with normalized stats and capacity info. NOTE: personal funds can only contain the authenticated user's OWN bots — use list_my_bots for roster-eligible strategies. This tool is for researching the broader bot ecosystem. Args: domain: Filter by domain (e.g. "eth_usdc"). Returns a JSON array of bot entries with gamified card ratings.

輸入參數domain

list_my_bots

List the authenticated user's OWN bots eligible for a personal fund roster. Personal funds can NEVER contain another user's bots — this returns only the caller's own personal + incubating + live bots with live engine stats and gamified card ratings. Args: domain: Filter by domain (e.g. "eth_usdc"). Returns a JSON array of the user's bots.

輸入參數domain

get_fund_positions

Get open positions for a fund's roster bots. Args: fund_id: The fund's ID. Returns a JSON array of open positions with entry/exit prices and PnL.

輸入參數fund_id必填

get_fund_trades

Get closed trade history for a fund's roster bots. Args: fund_id: The fund's ID. limit: Max trades to return (default 50). offset: Pagination offset. Returns a JSON array of closed trades.

輸入參數limitoffsetfund_id必填

get_fund_performance

Get performance snapshots for a fund's P&L graph. Args: fund_id: The fund's ID. limit: Max snapshots to return (default 100). Returns a JSON time-series of AUM/PnL snapshots.

輸入參數limitfund_id必填

get_fund_live_pnl

Build a real-time PnL chart from closed positions for a fund's roster. Args: fund_id: The fund's ID. Returns a JSON series of cumulative PnL points.

輸入參數fund_id必填

get_fund_analytics

Get real-time analytics for a fund dashboard. Args: fund_id: The fund's ID. Returns fund analytics: allocation breakdown, per-bot performance, risk metrics, and benchmark comparison.

輸入參數fund_id必填

run_fund_historical_test

Simulate how a roster of bots would have performed historically. Queries each bot's closed positions over the available historical period and combines them (weighted) into a single PnL time-series with diagnosis. Rate limited: 1 request per 30 seconds per user. Args: roster: List of {"bot_id": str, "weight_pct": float} entries. initial_capital: Starting capital for the simulation (default 10000). Returns the simulated PnL time-series and diagnosis.

輸入參數roster必填initial_capital

generate_fund_report_card

Generate a new report card for a fund (immutable once saved). Args: fund_id: The fund's ID. Returns the generated report card with grades and analysis.

輸入參數fund_id必填

get_fund_report_card

Get the latest report card for a fund. Args: fund_id: The fund's ID. Returns the latest immutable report card, or null if none exists.

輸入參數fund_id必填

get_manager_profile

Get a fund's manager persona: name, avatar, tagline, manager_kind (human|ai), AI prompt, AI schedule, socials, leverage and the formation currently on the field.

輸入參數fund_id必填

set_manager_profile

Set the manager persona shown on the fund's PUBLIC page. Args: fund_id: Your fund. persona_name: Display name, e.g. "Grandma Prudence". avatar: One emoji, e.g. "👵". tagline: One line under the name. manager_kind: "human" or "ai". With "ai", the platform's AI loop can run the fund on a schedule using ai_prompt. philosophy: The fund's investment philosophy (public). ai_prompt: System prompt for the platform AI manager (public). ai_enabled: Let the platform AI decide on a schedule. ai_cadence_hours: How often the AI decides (1-168). ai_use_search: Let the AI read live news via grounded search. socials: {"twitter": "@x", "website": "...", "discord", "telegram", "github", "youtube"}.

輸入參數avatarfund_id必填socialstaglineai_promptai_enabledphilosophymanager_kindpersona_nameai_use_searchai_cadence_hours

list_formation_templates

Ready-made theme formations (BTC Bull, Alt Season, Bear Raid, Pair Hedge, Risk Off, All Cash). Add one with create_formation(template_key=...).

無需輸入參數。

list_directional_bots

Directional building-block bots: always long / always short BTC, ETH, SOL. Pure exposure, no edge — use them to express a market view in a formation (e.g. news is bullish for BTC -> a formation heavy in dir_long_btc). Allowed in personal and standard funds.

無需輸入參數。

list_formations

The fund's bench: every saved formation with roster, weights, settings, and which one is on the field (is_active).

輸入參數fund_id必填

create_formation

Save a formation on the fund's bench. Args: fund_id: Your fund. name: Formation name, e.g. "Iran Oil Shock". roster: [{"bot_id": "dir_long_btc", "weight_pct": 60}, ...]. Weights under 100 total leave the rest in cash. Empty list = all cash. Shares may not add up to more than 100. emoji: Optional emoji. description: When you'd play it. leverage: 1-20x for this formation (applied to new positions). sizing: "weights" = size by your weights (default), "router" = the router's Kelly sizing (skips bots without history). template_key: Start from a template instead (see list_formation_templates). from_current: Snapshot the live roster + settings instead. rationale: REQUIRED — why this config exists. Published on the fund's public manager's log.

輸入參數nameemojirostersizingfund_id必填leveragerationaledescriptionfrom_currenttemplate_key

update_formation

Edit a saved formation. Changes take effect next time it goes on the field. rationale is REQUIRED — why you changed it. Published on the manager's log.

輸入參數nameemojirostersizingfund_id必填leveragerationaledescriptionformation_id必填

delete_formation

Delete a formation from the bench (not the one on the field). rationale is REQUIRED — why you're deleting it. Published on the manager's log.

輸入參數fund_id必填rationale必填formation_id必填

switch_formation

Put a formation on the field — the manager's main move. Bots in both lineups keep their positions. Departing bots: mode "flip" closes their positions at market now; "drain" lets them exit on their own rules. Arriving bots go through the normal fund rules; any rejected are listed in the result. The rationale is published on the fund's public manager's log — write it for the fund's followers.

輸入參數modefund_id必填rationale必填formation_id必填

post_fund_note

Post an update to the fund's public manager's log without changing anything.

輸入參數text必填fund_id必填headline

get_fund_log

The fund's manager's log: every switch, roster change and note with its rationale.

輸入參數limitfund_id必填

get_public_fund_page

Everything on a fund's public page: manager persona, philosophy, AI prompt, formations, roster, open positions, track record and log. Works for any public fund, not just yours.

輸入參數fund_id必填

list_managers

Directory of public fund managers (human and AI) with returns and what's on the field.

輸入參數limit

run_ai_manager

Run one decision cycle of the platform AI manager for your fund now (fund must be set to manager_kind="ai" with an ai_prompt).

輸入參數fund_id必填

tag_team_info

Get the authenticated user's Tag Team session info. Tag Team is a daily paper-trading competition: you get $10k paper capital split 70% human / 30% Co-Pilot bot. Make manual trades, deploy the Co-Pilot after 3 closed manual trades, and your combined PnL is scored on the daily leaderboard. Returns session state, open positions, bot status, and rank.

無需輸入參數。

tag_team_templates

List all available Co-Pilot templates (momentum, scalper, etc.). Each template defines the Co-Pilot bot's signal logic and tunable parameter ranges. Bot params carry over between days for the same template — trained settings persist.

無需輸入參數。

tag_team_leaderboard

Get the daily Tag Team leaderboard. Args: date: Optional date filter (YYYY-MM-DD). Defaults to today. Scoring needs 5+ human trades AND 5+ bot trades to qualify. score = sharpe x trade_factor x (1 + win_bonus).

輸入參數date

tag_team_weekly

Get weekly championship standings (best 5 daily scores per user).

無需輸入參數。

tag_team_history

Get the authenticated user's past Tag Team sessions with scores.

無需輸入參數。

tag_team_tier

Get the authenticated user's Tag Team tier and stats. Tiers: Rookie (0) -> Apprentice (10) -> Trader (50) -> Veteran (150) -> Expert (500) -> Master (1000+), based on total trades across all sessions (persists across days).

無需輸入參數。

tag_team_badges

Get the authenticated user's Tag Team badges. Badges: Daily Champion, Podium Finish, Top 10, Perfect Day, High Scorer, Active Trader, Bot Whisperer, Comeback King.

無需輸入參數。

get_vault_status

Get the authenticated user's Vault state. The Vault is a regime-aware allocator: in strong markets most capital holds BTC/ETH/SOL; when the market weakens it rotates into savings and funding arbitrage. Returns current regime, allocation weights, and sleeve holdings.

無需輸入參數。

get_vault_history

Get the Vault's regime switch history for the timeline. Returns a JSON array of past regime transitions with timestamps.

無需輸入參數。

版本歷史

1
  1. v1.0.0最新Sep 16, 2026

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