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al-one

MCP Server for stock and crypto

获取加密货币分析报告

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)
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions the tool is '对分析加密货币非常有用' (very useful for analyzing cryptocurrencies), but this is vague and doesn't disclose key behavioral traits like whether it's read-only, requires authentication, has rate limits, or what the output format might be. The description adds minimal context beyond the basic purpose.

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

Conciseness4/5

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

The description is concise with two short sentences, front-loading the core purpose. However, the second sentence '此工具对分析加密货币非常有用,推荐使用' (this tool is very useful for analyzing cryptocurrencies, recommended to use) adds little value and could be considered redundant or promotional, slightly reducing efficiency.

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

Completeness2/5

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

Given no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits, output format, error handling, or how it integrates with other tools. For a tool that likely provides analysis reports, more context is needed to understand its full functionality and limitations.

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

Parameters3/5

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

The input schema has 1 parameter with 100% description coverage, clearly documenting the 'symbol' parameter. The description doesn't add any parameter-specific information beyond what the schema provides, such as examples or constraints. With high schema coverage, the baseline score is 3, as the description doesn't compensate but also doesn't detract.

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

Purpose3/5

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

The description states the tool '获取币安对加密货币的AI分析报告' (gets Binance's AI analysis report for cryptocurrencies), which provides a clear verb ('获取') and resource ('AI分析报告'). However, it doesn't distinguish this tool from potential sibling tools like 'stock_indicators_a' or 'trading_suggest' that might also provide analysis, and the phrase '对分析加密货币非常有用' (very useful for analyzing cryptocurrencies) is somewhat vague rather than specific.

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

Usage Guidelines2/5

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

The description includes '推荐使用' (recommended to use), which implies a general endorsement but doesn't specify when to use this tool versus alternatives. There's no guidance on context, prerequisites, or exclusions, such as whether it's for real-time analysis, historical data, or how it differs from other analysis tools in the sibling list.

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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