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MCP Server for stock and crypto

获取加密货币分析报告

binance_ai_report

Retrieves AI analysis reports from Binance for cryptocurrencies. Enter a symbol like BTC or ETH to get the report.

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

  • The main handler function implementing the binance_ai_report tool. It calls Binance's AI report API and extracts translated module overviews and point contents.
    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)
  • The tool is registered with FastMCP using the @mcp.tool decorator, with title and description in Chinese.
    @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",
    )
  • Input schema: accepts a single 'symbol' parameter (default 'BTC') with Pydantic Field describing it as a cryptocurrency symbol in format like BTC or ETH.
    def binance_ai_report(
        symbol: str = Field("BTC", description="加密货币币种,格式: BTC 或 ETH"),
    ):
Behavior2/5

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It does not mention whether the operation is read-only, requires authentication, has rate limits, or what the report output contains. This is a significant gap for a data retrieval tool.

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 short with two sentences. However, the second sentence ('此工具对分析加密货币非常有用,推荐使用') is subjective and does not add factual value, making it slightly less concise than optimal.

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 the tool's simplicity (one parameter, no output schema, no annotations), the description is incomplete. It fails to explain what the AI report contains, how to use the result, or any limitations. Sibling tools provide alternative crypto data, but no clarification is given.

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?

Schema description coverage is 100% for the single parameter, so the base score is 3. The description adds no extra meaning beyond the schema's parameter description, which already explains the symbol format. No additional value from the description.

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

Purpose4/5

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

The description clearly states the tool retrieves Binance's AI analysis report for cryptocurrencies, specifying the verb '获取' (get) and resource. However, it does not differentiate this tool from sibling tools like okx_prices or trading_suggest, which also deal with cryptocurrencies.

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 offers no guidance on when to use this tool vs alternatives. It merely says 'very useful, recommended to use' without providing context or exclusion criteria for other crypto analysis tools.

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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