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al-one

MCP Server for stock and crypto

binance_ai_report

Generate AI-powered cryptocurrency analysis reports from Binance to inform investment decisions and market strategies.

Instructions

获取币安对加密货币的AI分析报告,此工具对分析加密货币非常有用,推荐使用

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNo加密货币币种,格式: BTC 或 ETHBTC

Implementation Reference

  • Handler function decorated with @mcp.tool, defining the schema via Field, and implementing the logic to fetch and parse Binance AI report for the given cryptocurrency symbol.
    @mcp.tool(
        title="获取加密货币分析报告",
        description="获取币安对加密货币的AI分析报告,此工具对分析加密货币非常有用,推荐使用",
    )
    def binance_ai_report(
        symbol: str = Field("BTC", description="加密货币币种,格式: BTC 或 ETH"),
    ):
        res = requests.post(
            f"{BINANCE_BASE_URL}/bapi/bigdata/v3/friendly/bigdata/search/ai-report/report",
            json={
                'lang': 'zh-CN',
                'token': symbol,
                'symbol': f'{symbol}USDT',
                'product': 'web-spot',
                'timestamp': int(time.time() * 1000),
                'translateToken': None,
            },
            headers={
                'User-Agent': USER_AGENT,
                'Referer': f'https://www.binance.com/zh-CN/trade/{symbol}_USDT?type=spot',
                'lang': 'zh-CN',
            },
            timeout=20,
        )
        try:
            resp = res.json() or {}
        except Exception:
            try:
                resp = json.loads(res.text.strip()) or {}
            except Exception:
                return res.text
        data = resp.get('data') or {}
        report = data.get('report') or {}
        translated = report.get('translated') or report.get('original') or {}
        modules = translated.get('modules') or []
        txts = []
        for module in modules:
            if tit := module.get('overview'):
                txts.append(tit)
            for point in module.get('points', []):
                txts.append(point.get('content', ''))
        return '\n'.join(txts)

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