systemr

Build AI trading agents with institutional-grade risk management.

Install

pip install systemr

Requires Python 3.9 or higher. The only dependency is httpx.

Your first trade gate

from systemr import SystemRClient

client = SystemRClient(api_key="sr_agent_...")

gate = client.pre_trade_gate(
    symbol="AAPL",
    direction="long",
    entry_price="185.50",
    stop_price="180.00",
    equity="100000",
)

if gate["gate_passed"]:
    print(f"Buy {gate['sizing']['shares']} shares of AAPL")
    print(f"Risk: ${gate['sizing']['risk_amount']}")

Five lines of code. Position sizing, risk validation, and system health in a single call for $0.01.

Chat

Talk to your agent in natural language. The LLM interprets your intent and calls the right tools.

from systemr import SystemRClient

client = SystemRClient(api_key="sr_agent_...")

# Ask a question — the agent picks the right tools
resp = client.chat("What's my current G-score? I've had these R-multiples: 1.5, -1.0, 2.0, -0.5, 1.8")
print(resp["text"])
print(f"Credits used: ${resp['credits_used']}")

# Continue the conversation
resp = client.chat("Run a Monte Carlo on those same trades", session_id=resp.get("session_id"))
print(resp["text"])

BYOK (Bring Your Own Key)

Pass your own Anthropic or OpenAI API key to skip LLM charges. Tool calls are still billed at standard rates.

# BYOK at client level — applies to all chat() calls
client = SystemRClient(
    api_key="sr_agent_...",
    external_api_key="sk-ant-..."  # your Anthropic key
)
resp = client.chat("Size a long AAPL position, entry 185.50 stop 180")
# LLM cost: $0 (your key). Tool cost: standard rate.

# Or BYOK per request
resp = client.chat("Detect the current regime for BTC", external_api_key="sk-ant-...")

What you get

55 tools across 8 categories. 25 brokers and exchanges. Usage-based — pay what you use via Stripe, SOL, USDC, USDT, PYUSD, or OSR.

Category	Count	Highlights
Core	4	Position sizing, risk validation, performance evaluation
Analysis	18	Monte Carlo, Kelly criterion, drawdown, equity curves
Intelligence	11	Regime detection, patterns, volatility surface, Greeks
Planning	4	Options sizing, futures sizing, trade plan builders
Data	3	P&L calculation, expected value, compliance
System	5	Signal scoring, margin, scanner evaluation
Compound	2	Pre-trade gate, full system assessment
Journal	1	Trade journaling with R-multiples
Memory and ML	7	Persistent memory, behavioral analytics, ML prediction

Connect to 25 brokers including IBKR, Schwab, Binance, Coinbase, Alpaca, Kraken, dYdX, Polymarket, and more.

Tools

Every tool is callable via client.call_tool("tool_name", **kwargs).

Core (4 tools)

Tool	Price	Description
`calculate_position_size`	$0.003	G-formula position sizing. Returns shares, risk amount, notional value, and 1R dollar amount.
`check_trade_risk`	$0.004	Iron Fist risk validation. Checks position limits, daily loss limits, correlation rules. Returns approval, score (0 to 100), errors, warnings.
`evaluate_performance`	$0.10 / $0.50 / $1.00	G-score performance analysis in three tiers: basic (G metric + verdict), full (G + rolling G + System R Score), comprehensive (all metrics + impact analysis).
`get_pricing`	Free	Returns current prices for every operation on the platform.

Analysis (18 tools)

Tool	Price	Description
`analyze_drawdown`	$0.004	Drawdown profile analysis. Max drawdown, drawdown duration, recovery metrics.
`run_monte_carlo`	$0.006	Monte Carlo simulation. 1,000 equity path projections with percentile bands.
`calculate_kelly`	$0.004	Kelly criterion calculation. Optimal bet fraction, half-Kelly recommendation.
`find_variance_killers`	$0.004	Identifies the specific trades dragging your G-metric down.
`analyze_win_loss`	$0.004	Win/loss distribution. Win rate, average win R, average loss R, payoff ratio.
`run_what_if`	$0.004	Scenario analysis. What happens to your G if you remove certain trades or change parameters.
`calculate_confidence`	$0.004	Statistical confidence intervals for your edge estimate.
`analyze_consistency`	$0.004	Rolling consistency metrics. Measures how stable your edge is over time.
`analyze_correlation`	$0.006	Cross-trade correlation analysis. Detects clustering and serial dependency in outcomes.
`analyze_distribution`	$0.004	R-multiple distribution analysis. Skew, kurtosis, normality tests.
`analyze_recovery`	$0.004	Recovery analysis. Time to recover from drawdowns, recovery factor.
`calculate_risk_adjusted`	$0.004	Risk-adjusted returns. Sharpe, Sortino, Calmar ratios from R-multiples.
`analyze_segmentation`	$0.006	Segment performance by direction, asset, time of day, day of week.
`analyze_execution_quality`	$0.006	Execution quality scoring. Slippage analysis, fill rate, MFE/MAE ratios.
`analyze_peak_valley`	$0.004	Peak-to-valley analysis on the equity curve.
`calculate_rolling_g`	$0.004	Rolling G-metric over sliding windows. Shows how your edge evolves.
`calculate_system_r_score`	$0.004	System R Score: A/B/C/D/F grade based on composite G-metrics.
`calculate_equity_curve`	$0.004	Equity curve from R-multiples. Total return, max drawdown, CAGR.

Intelligence (11 tools)

Tool	Price	Description
`detect_regime`	$0.006	Market regime detection. Identifies trending, ranging, volatile, or quiet regimes.
`detect_patterns`	$0.006	Chart pattern recognition. Head-and-shoulders, double tops, triangles, flags.
`detect_structural_break`	$0.006	Structural break detection in price series. Identifies regime transitions.
`analyze_trend_structure`	$0.006	Trend structure analysis. Higher highs/lows, trend strength, pullback quality.
`calculate_indicators`	$0.004	Technical indicator calculation. RSI, MACD, Bollinger, ATR, and more.
`analyze_price_structure`	$0.006	Price structure analysis. Support/resistance levels, pivot points, price channels.
`analyze_correlations`	$0.006	Multi-asset correlation matrix. Cross-asset relationships and divergences.
`analyze_liquidity`	$0.006	Liquidity analysis. Bid-ask spreads, depth, volume profiles.
`analyze_greeks`	$0.006	Options Greeks analysis. Delta, gamma, theta, vega for entire chains.
`analyze_iv_surface`	$0.008	Implied volatility surface mapping. Skew, term structure, vol smile.
`analyze_futures_curve`	$0.006	Futures curve analysis. Contango/backwardation, roll yield, basis.

Planning (4 tools)

Tool	Price	Description
`calculate_options_size`	$0.004	Options position sizing. Contract count based on premium risk and Greeks.
`calculate_futures_size`	$0.004	Futures position sizing. Contract count based on margin and tick value.
`build_options_plan`	$0.008	Options trade plan builder. Strategy selection, strike selection, risk/reward profile.
`build_futures_plan`	$0.008	Futures trade plan builder. Entry, stop, target with margin requirements.

Data (3 tools)

Tool	Price	Description
`calculate_pnl`	$0.003	P&L calculation. Gross, net, fees, R-multiple from entry/exit/quantity.
`calculate_expected_value`	$0.003	Expected value calculation from win rate and average win/loss.
`check_compliance`	$0.004	Compliance check against configurable rule sets. Position limits, concentration, restricted lists.

System (5 tools)

Tool	Price	Description
`calculate_equity_curve`	$0.004	Build equity curve from R-multiples with a starting balance.
`score_signal`	$0.003	Signal quality scoring. Confluence, regime alignment, volume confirmation. Returns confidence and quality score 0 to 100.
`analyze_trade_outcome`	$0.003	Post-trade outcome classification. WIN/LOSS/BREAKEVEN, efficiency score, edge captured.
`calculate_margin`	$0.002	Margin requirement calculation by asset class and direction.
`evaluate_scanner`	$0.005	Evaluate a market scanner against multiple symbols and conditions.

Compound (2 tools)

Tool	Price	Description
`pre_trade_gate`	$0.01	The tool you call before every trade. Combines position sizing, risk validation, and system health into a single gate. Returns `gate_passed` (bool) so your agent can make a go/no-go decision in one call.
`assess_trading_system`	$2.00	Comprehensive trading system assessment. Runs G-metrics, win/loss, Kelly criterion, Monte Carlo, drawdown analysis, and what-if scenarios. Returns a verdict: STRONG_SYSTEM, VIABLE_SYSTEM, MARGINAL_SYSTEM, or FAILING_SYSTEM.

Journal (1 tool)

Tool	Price	Description
`record_trade_outcome`	$0.003	Record a completed trade to your agent's journal. Symbol, direction, entry, exit, stop, quantity, R-multiple, P&L, notes. Journal queries (trades, stats, R-multiples) are free REST endpoints.

Memory and ML (7 tools)

Tool	Price	Description
`store_memory`	$0.002	Store a key-value memory entry for your agent. Persistent across sessions.
`search_memory`	$0.002	Search stored memories by key or semantic query.
`get_trading_biases`	$0.004	Detect behavioral biases from trade history: disposition effect, recency bias, overtrading, loss aversion.
`get_behavioral_fingerprint`	$0.006	Generate a behavioral fingerprint for the agent. Risk appetite, decision speed, adaptability profile.
`predict_trajectory`	$0.008	ML-based trajectory prediction. Projects future performance based on historical patterns.
`detect_anomalies`	$0.006	Anomaly detection in trading behavior. Flags unusual position sizes, frequency spikes, style drift.
`cluster_trades`	$0.006	Unsupervised clustering of trades by outcome, duration, asset, and strategy characteristics.

Brokers and Exchanges

25 brokers and exchanges across every major market.

Traditional Brokers

Broker	Markets	API
Interactive Brokers (IBKR)	Stocks, Options, Futures, Forex	TWS / Client Portal
Charles Schwab	Stocks, Options, ETFs	Schwab API
Alpaca	Stocks, Crypto	Alpaca v2
Tradier	Stocks, Options	Tradier REST
Tastytrade	Stocks, Options, Futures	Tastytrade API
TradeStation	Stocks, Options, Futures	TradeStation v3
E*TRADE	Stocks, Options, ETFs	E*TRADE v1

Forex

Broker	Markets	API
OANDA	Forex, CFDs	OANDA v20

Crypto Exchanges

Exchange	Markets	API
Binance	Spot, Futures, Options	Binance REST/WS
Bybit	Spot, Perps, Options	Bybit v5
OKX	Spot, Perps, Options, Futures	OKX v5
Coinbase	Spot	Coinbase Advanced
Kraken	Spot, Futures	Kraken REST
Deribit	Options, Futures	Deribit v2
KuCoin	Spot, Futures	KuCoin v2
Gate.io	Spot, Futures	Gate.io v4
Gemini	Spot	Gemini v1
Bitfinex	Spot, Margin	Bitfinex v2
Aster	Spot	Aster REST

DeFi Protocols

Protocol	Markets	Chain
Hyperliquid	Perps	Hyperliquid L1
dYdX	Perps	dYdX Chain
Drift	Perps, Spot	Solana

Prediction Markets

Platform	Markets	Type
Polymarket	Binary outcomes	Polygon
Kalshi	Binary outcomes, Events	Regulated exchange

Broker Connection Example

import requests

headers = {"Authorization": "Bearer sr_agent_..."}
base = "https://agents.systemr.ai"

# Connect to Binance
resp = requests.post(f"{base}/v1/broker/connect", headers=headers, json={
    "broker": "binance",
    "credentials": {
        "api_key": "your_binance_api_key",
        "api_secret": "your_binance_api_secret",
    },
})
print(resp.json())  # {"status": "connected", "broker": "binance"}

# Check positions
resp = requests.get(f"{base}/v1/broker/positions", headers=headers)
positions = resp.json()
for pos in positions["positions"]:
    print(f"{pos['symbol']}: {pos['quantity']} @ {pos['avg_price']}")

# Place an order
resp = requests.post(f"{base}/v1/broker/order", headers=headers, json={
    "symbol": "BTCUSDT",
    "side": "BUY",
    "type": "LIMIT",
    "quantity": "0.01",
    "price": "65000.00",
})
print(resp.json())  # {"order_id": "...", "status": "NEW"}

Workflows

1. Pre-Trade Gate (call before every trade)

One call, three checks: position sizing, risk validation, and system health.

from systemr import SystemRClient

client = SystemRClient(api_key="sr_agent_...")

gate = client.pre_trade_gate(
    symbol="AAPL",
    direction="long",
    entry_price="185.50",
    stop_price="180.00",
    equity="100000",
    r_multiples=["1.5", "-1.0", "2.0", "-0.5", "1.8", "0.8", "-0.3"],
)

if gate["gate_passed"]:
    shares = gate["sizing"]["shares"]
    risk = gate["sizing"]["risk_amount"]
    print(f"APPROVED: Buy {shares} shares, risking ${risk}")
    if gate.get("system_health"):
        print(f"System G: {gate['system_health']['g']}")

Cost: $0.01

2. Backtest Diagnostic (6-tool chain)

Feed your backtest R-multiples and get a complete system analysis: equity curve, grade, drawdown, Monte Carlo projection, variance killers, and win/loss distribution.

diag = client.run_backtest_diagnostic(
    r_multiples=[
        "1.5", "-1.0", "2.0", "-0.5", "1.8",
        "0.8", "-0.3", "2.5", "-1.0", "1.2",
        "0.5", "-0.8", "1.1", "-0.2", "3.0",
    ],
    starting_equity="100000",
)

print(f"Grade: {diag['system_r_score']['grade']}")
print(f"Total return: {diag['equity_curve']['total_return']}")
print(f"Max drawdown: {diag['equity_curve']['max_drawdown_pct']}")
print(f"Monte Carlo median: ${diag['monte_carlo']['median_final_equity']}")
print(f"Variance killers: {len(diag['variance_killers'].get('killers', []))} trades")
print(f"Win rate: {diag['win_loss']['win_rate']}")

Cost: ~$0.032

3. Full System Assessment

Quarterly system review. Runs G-metrics, win/loss analysis, Kelly criterion, Monte Carlo, drawdown, and what-if scenarios in a single compound call.

assessment = client.assess_system(
    r_multiples=[
        "1.5", "-1.0", "2.0", "-0.5", "1.8",
        "0.8", "-0.3", "2.5", "-1.0", "1.2",
        "0.5", "-0.8", "1.1", "-0.2", "3.0",
        "-1.0", "0.7", "1.5", "-0.6", "2.1",
    ],
    starting_equity="100000",
)

print(f"Verdict: {assessment['verdict']}")
# STRONG_SYSTEM, VIABLE_SYSTEM, MARGINAL_SYSTEM, or FAILING_SYSTEM

print(f"G metric: {assessment['g_metrics']['g']}")
print(f"Kelly fraction: {assessment['kelly']['kelly_fraction']}")
print(f"Half-Kelly: {assessment['kelly']['half_kelly']}")
print(f"Monte Carlo median: ${assessment['monte_carlo']['median_final_equity']}")
print(f"Max drawdown: {assessment['drawdown']['max_drawdown_pct']}")

Cost: $2.00

4. Market Intelligence Scan

Scan a watchlist for technical conditions, then score each matching signal for quality and confidence.

scan = client.run_market_scan(
    symbols=["AAPL", "MSFT", "GOOGL", "NVDA", "TSLA"],
    conditions=["rsi_oversold", "volume_spike"],
    market_data={
        "AAPL": {
            "indicators": {"rsi_14": "28", "relative_volume": "2.1"},
            "current_price": "180.00", "regime": "RANGING", "atr": "3.50",
        },
        "MSFT": {
            "indicators": {"rsi_14": "55", "relative_volume": "0.8"},
            "current_price": "400.00", "regime": "TRENDING_UP", "atr": "5.00",
        },
        "GOOGL": {
            "indicators": {"rsi_14": "22", "relative_volume": "1.8"},
            "current_price": "155.00", "regime": "TRENDING_DOWN", "atr": "4.20",
        },
    },
)

for signal in scan["scored_signals"]:
    print(f"{signal['symbol']}: quality={signal['quality_score']}/100, "
          f"confidence={signal['signal_confidence']}")

Cost: $0.005 + $0.003 per matching signal

5. Memory-Assisted Trading

Agents can persist memories across sessions and use behavioral analytics to improve over time.

# Store a trading insight
client.call_tool("store_memory",
    key="aapl_earnings_pattern",
    value="AAPL tends to gap down after earnings then recover within 3 days. "
          "Best entry is day 2 close if RSI < 35.",
)

# Later: recall it before an AAPL earnings trade
memories = client.call_tool("search_memory", query="aapl earnings")
print(memories)

# Check your behavioral biases
biases = client.call_tool("get_trading_biases",
    r_multiples=["1.5", "-1.0", "2.0", "-0.5", "0.3", "-2.0", "0.8"],
    trade_durations=["120", "30", "240", "15", "60", "180", "90"],
)
print(f"Detected biases: {biases['biases']}")

# Get your behavioral fingerprint
fingerprint = client.call_tool("get_behavioral_fingerprint",
    r_multiples=["1.5", "-1.0", "2.0", "-0.5", "1.8"],
    trade_durations=["120", "30", "240", "15", "60"],
    position_sizes=["100", "50", "200", "75", "150"],
)
print(f"Risk appetite: {fingerprint['risk_appetite']}")
print(f"Adaptability: {fingerprint['adaptability']}")

Cost: $0.002 to $0.006 per call

Billing

Usage-based pricing. Pay what you use, no subscriptions. New accounts receive a $5 signup credit.

Billing is at the owner level: one balance shared across all your API keys. You can set per-key spending limits (daily/monthly caps, operation restrictions).

LLM pricing

Model	Input	Output
Sonnet	$9 / 1M tokens	$45 / 1M tokens
Opus	$45 / 1M tokens	$225 / 1M tokens
BYOK	$0	$0

BYOK: pass your own Anthropic or OpenAI key via external_api_key. No LLM charge — tool calls still billed at standard rates.

Payment methods

Method	How	Notes
Stripe	`POST /v1/billing/checkout`	Card payment, returns checkout URL
OSR	`POST /v1/billing/deposit-osr`	70% burned / 30% retained, live market price. Presale buyers get permanent 20% discount.
SOL	`POST /v1/billing/deposit-sol`	Solana native token
USDC	`POST /v1/billing/deposit-usdc`	Circle USDC on Solana
USDT	`POST /v1/billing/deposit-usdt`	Tether USDT on Solana
PYUSD	`POST /v1/billing/deposit-pyusd`	PayPal USD on Solana

Crypto deposits require a tx_signature (Solana transaction signature) and amount.

Wallet linking

import requests

headers = {"Authorization": "Bearer sr_agent_..."}
base = "https://agents.systemr.ai"

# Link your Solana wallet
requests.post(f"{base}/v1/agents/link-wallet", headers=headers, json={
    "wallet_address": "YourSolanaPublicKey...",
})

# Deposit OSR tokens
requests.post(f"{base}/v1/billing/deposit-osr", headers=headers, json={
    "tx_signature": "your_solana_tx_signature",
    "amount": "10000",
})

# Check balance
resp = requests.get(f"{base}/v1/billing/balance", headers=headers)
print(resp.json())  # {"balance": "...", "currency": "USDC"}

OSR presale discount

Agents whose linked wallet participated in the OSR token presale receive a permanent 20% discount on every tool call. The discount is verified on-chain through the linked Solana wallet. The wallet is the identity.

API Reference

All endpoints are prefixed with https://agents.systemr.ai/v1.

Agent Management

Method	Endpoint	Description
POST	`/agents/register`	Register a new agent. Returns API key.
GET	`/agents/me`	Get current agent info.
GET	`/agents/list`	List all agents under your ownership.
PUT	`/agents/mode`	Change agent mode (sandbox, live, suspended, terminated).
POST	`/agents/link-wallet`	Link a Solana wallet to the agent.

Billing

Method	Endpoint	Description
GET	`/billing/balance`	Current balance in USDC.
POST	`/billing/deposit`	Generic deposit.
POST	`/billing/deposit-osr`	Deposit OSR tokens for compute credits.
POST	`/billing/deposit-sol`	Deposit SOL for compute credits.
POST	`/billing/deposit-usdc`	Deposit USDC for compute credits.
POST	`/billing/deposit-usdt`	Deposit USDT for compute credits.
POST	`/billing/deposit-pyusd`	Deposit PYUSD for compute credits.
GET	`/billing/transactions`	Transaction history.
GET	`/billing/usage`	Usage summary grouped by operation.
GET	`/billing/pricing`	Current operation pricing.

Broker

Method	Endpoint	Description
GET	`/broker/supported`	List supported brokers and exchanges.
POST	`/broker/connect`	Connect broker credentials.
POST	`/broker/disconnect`	Disconnect a broker.
GET	`/broker/account`	Broker account info and balances.
GET	`/broker/positions`	Current open positions.
POST	`/broker/order`	Submit an order.
POST	`/broker/cancel`	Cancel an open order.
GET	`/broker/orders`	List open and recent orders.

Tools

Method	Endpoint	Description
POST	`/tools/call`	Call any tool by name with arguments.
GET	`/tools/list`	List all available tools with schemas and pricing.

Support

Method	Endpoint	Description
POST	`/support/feedback`	Submit general feedback.
POST	`/support/ticket`	Open a support ticket.
POST	`/support/suggestion`	Submit a feature suggestion.
POST	`/support/enterprise`	Enterprise inquiry.
POST	`/support/bug`	Report a bug.
GET	`/support/tickets`	List your support tickets.
GET	`/support/ticket/{id}`	Get a specific ticket.

Guardian

Method	Endpoint	Description
GET	`/guardian/status`	Guardian system status for your agent.
GET	`/guardian/report`	Full Guardian risk report.

Trust

Method	Endpoint	Description
GET	`/trust/trust-score`	Your agent's trust score.
GET	`/trust/tier-policies`	Trust tier requirements and policies.
GET	`/trust/access-policy`	Current access policy for your agent's trust tier.

Leaderboard

Method	Endpoint	Description
GET	`/leaderboard`	Agent performance leaderboard.

Graduation

Method	Endpoint	Description
GET	`/graduation/check`	Check if your agent qualifies for tier promotion.
POST	`/graduation/apply`	Apply for tier promotion.

Audit

Method	Endpoint	Description
GET	`/audit/trail`	Audit trail for your agent's actions.
GET	`/audit/compliance-check`	Run a compliance check.

Onboarding

Method	Endpoint	Description
POST	`/onboarding/verify`	Verify agent registration.
GET	`/onboarding/quickstart`	Quickstart guide and next steps.

MCP

System R is available as an MCP (Model Context Protocol) server for direct integration with LLM clients like Cursor, Windsurf, and other MCP-compatible tools.

Remote server (recommended)

Add this to your MCP client configuration:

{
  "mcpServers": {
    "systemr": {
      "transport": "sse",
      "url": "https://agents.systemr.ai/mcp/sse",
      "headers": {
        "X-API-Key": "sr_agent_..."
      }
    }
  }
}

Local stdio server

Run a local proxy:

pip install systemr "mcp>=1.8.0"
SYSTEMR_API_KEY=sr_agent_... python -m systemr.mcp_server

Configuration for local stdio mode:

{
  "mcpServers": {
    "systemr": {
      "command": "python",
      "args": ["-m", "systemr.mcp_server"],
      "env": {
        "SYSTEMR_API_KEY": "sr_agent_..."
      }
    }
  }
}

Streamable HTTP

For clients that support the streamable HTTP transport:

{
  "mcpServers": {
    "systemr": {
      "transport": "streamable-http",
      "url": "https://agents.systemr.ai/mcp/sse",
      "headers": {
        "X-API-Key": "sr_agent_..."
      }
    }
  }
}

All 55 tools are available through MCP with full input schemas, descriptions, and pricing metadata.

Links


Agent Platform	agents.systemr.ai
OSR Protocol	osrprotocol.com
System R AI	systemr.ai
PyPI	pypi.org/project/systemr
GitHub	github.com/System-R-AI/systemr-python
X	@OsrProtocol

Name		Name	Last commit message	Last commit date
Latest commit History 19 Commits
assets		assets
examples		examples
systemr		systemr
tests		tests
.gitignore		.gitignore
CHANGELOG.md		CHANGELOG.md
Dockerfile		Dockerfile
LICENSE		LICENSE
README.md		README.md
pyproject.toml		pyproject.toml
server.json		server.json

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systemr

Install

Your first trade gate

Chat

BYOK (Bring Your Own Key)

What you get

Tools

Core (4 tools)

Analysis (18 tools)

Intelligence (11 tools)

Planning (4 tools)

Data (3 tools)

System (5 tools)

Compound (2 tools)

Journal (1 tool)

Memory and ML (7 tools)

Brokers and Exchanges

Traditional Brokers

Forex

Crypto Exchanges

DeFi Protocols

Prediction Markets

Broker Connection Example

Workflows

1. Pre-Trade Gate (call before every trade)

2. Backtest Diagnostic (6-tool chain)

3. Full System Assessment

4. Market Intelligence Scan

5. Memory-Assisted Trading

Billing

LLM pricing

Payment methods

Wallet linking

OSR presale discount

API Reference

Agent Management

Billing

Broker

Tools

Support

Guardian

Trust

Leaderboard

Graduation

Audit

Onboarding

MCP

Remote server (recommended)

Local stdio server

Streamable HTTP

Links

License

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