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Bitget MCP — Crypto, DeFi & Macro Market Intelligence

backtest

Run historical backtests on trading strategies using VectorBT. Fetches OHLCV from exchange (ccxt), computes indicators (RSI/MACD/BB/EMA/ATR), evaluates entry/exit signals, simulates portfolio, returns structured metrics (return%, Sharpe, max drawdown, win rate, profit factor). Optionally generates equity curve chart. Supports pre-fetched OHLCV via ohlcv_json for coingecko/yfinance data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesrun=execute backtest, chart=regenerate chart from previous metrics
periodNoLookback period, e.g. '6m', '1y', '30d'. Default: 6m
exchangeNoExchange for OHLCV data. Default: binance
ohlcv_jsonNoPre-fetched OHLCV as JSON string (from coingecko/yfinance tools). Format: {"SYMBOL": [{"timestamp":ms,"open":...,"close":...}, ...]}
metrics_jsonNoFor action=chart: JSON metrics from a previous run.
generate_chartNoGenerate equity curve chart (requires playwright). Default: false
strategy_configNoJSON string with strategy config. Keys: name, symbols (list), timeframe, indicators (list of {name, params, key}), entry_conditions (list of {indicator, field, operator, value}), exit_conditions, direction (long/short/both), stop_loss_pct, take_profit_pct, trade_size_pct, fees.
starting_balanceNoInitial cash. Default: 100000

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description covers behavior: fetching OHLCV, computing indicators, evaluating signals, simulating portfolio, returning metrics, and optional chart generation requiring playwright. It omits potential errors or performance details but is generally transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a concise 3-sentence paragraph that front-loads the main purpose, then details the process, and ends with a special feature. No redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity and lack of output schema, the description provides a solid overview of inputs, process, and outputs. It mentions metric names and the chart requirement. Minor omissions include error handling and system dependencies (except playwright).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the description adds context by naming specific indicators, metrics, and the ability to use pre-fetched data. It complements the schema descriptions effectively.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it runs historical backtests using VectorBT, listing specific steps and outputs. It distinguishes itself from sibling data/analysis tools by focusing on backtesting and portfolio simulation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for backtesting trading strategies but does not explicitly mention when to avoid or provide alternatives among siblings. However, the context makes it clear this is the backtesting tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3/5.0
Disambiguation3/5

Multiple tools overlap in providing crypto price data (crypto_price, crypto_market, crypto_derivatives, global_assets) and news (news_feed, tradfi_news). While descriptions clarify some differences, agents may struggle to choose between similar tools.

Naming Consistency2/5

Tool names mix styles: some are simple nouns (backtest, cn_market), others compound nouns with underscores (crypto_derivatives, derivatives_sentiment). No consistent verb_noun pattern, making it harder to infer purpose from name alone.

Tool Count3/5

With 19 tools covering a broad domain (crypto, DeFi, macro), the count feels slightly high but justifiable. However, several tools could be merged to reduce overlap and improve navigability.

Completeness4/5

The tool set covers a wide range of market intelligence needs: price data, technical analysis, sentiment, macro indicators, news, and DeFi. Minor gaps like on-chain analytics or direct trading are acceptable given the intelligence focus.

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