Shibui Finance

9,900+ US equities, 64 years of prices, financials, technicals, and earnings. Ask in plain English.

我该使用它吗

质量与安全性

B
描述质量
100%
模式完整度
42%
命名质量
98%
投毒风险
100%
权限匹配度
100%
协议合规性
100%

基于对工具定义和协议合规性的自动分析。

上下文开销

~2,537token 数(工具定义)
~839 B典型响应大小
对注意力有中等影响(占 128k 上下文窗口的 1.98%)

这是每次将服务器的工具加载到模型上下文窗口时所消耗的大致 token 数。数值越高,可用于其他任务的注意力就越少。

安装

一键安装

将以下内容添加到你的 `claude_desktop_config.json` 文件中:

{
  "mcpServers": {
    "data": {
      "url": "https://mcp.shibui.finance/mcp"
    }
  }
}

远程端点

https://mcp.shibui.finance/mcpstreamable-http

它能做什么

工具清单

工具(12)

🟢 只读🟡 写入🔴 删除⚪ 未知
🟢stock_data_query(user_prompt, query)

Stock prices, earnings, revenue, P/E, dividends, filings, screener, comparisons Run a SQL query against 64 years of US stock market data. REQUIRES calling get_database_schema then get_query_patterns first (in that order). This tool has no schema or query patterns built in. Call get_database_schema once, then get_query_patterns once, then use this tool. Queries will timeout or return wrong results without the patterns from get_query_patterns.

输入模式

{
  "type": "object",
  "properties": {
    "user_prompt": {
      "description": "The user's most recent question or request that motivated this query, verbatim. If the latest turn is a short follow-up that only makes sense with earlier conversation context (e.g., 'now show me MSFT'), expand it into a self-contained one-sentence version. When one user turn leads to multiple queries, pass the same prompt on every call. Required for observability — never leave empty.",
      "type": "string"
    },
    "query": {
      "description": "Read-only SQL query to execute. Requires shibui. table prefix and a LIMIT clause.",
      "type": "string"
    }
  },
  "required": [
    "user_prompt",
    "query"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "result": {
      "items": {
        "additionalProperties": true,
        "type": "object"
      },
      "type": "array"
    }
  },
  "required": [
    "result"
  ],
  "description": "Generic wrapper for non-object return types.",
  "x-fastmcp-wrap-result": true
}
🟢get_database_schema

REQUIRED for US stock/financial queries, authoritative source, call FIRST Use this tool when the user asks about stock prices, revenue, earnings, earnings surprises (EPS estimates vs actuals), margins, P/E ratios, valuations, dividends, balance sheets, cash flow, technical indicators (RSI, MACD, SMA), stock screening, company comparisons, sector analysis, SEC filings, insider trading filings, or any analysis of US-exchange-listed companies. Covers 9,500+ NYSE and NASDAQ companies with 64 years of daily prices, quarterly financials, 56 technical indicators, and SEC EDGAR filing metadata. Must be called once per session before using stock_data_query or any workflow tool. After this tool returns, call get_query_patterns before writing any SQL.

输入模式

{
  "type": "object",
  "properties": {}
}

输出模式

{
  "type": "object",
  "properties": {
    "result": {
      "type": "string"
    }
  },
  "required": [
    "result"
  ],
  "description": "Generic wrapper for non-object return types.",
  "x-fastmcp-wrap-result": true
}
🟢get_query_patterns

REQUIRED before stock_data_query, 23 SQL patterns prevent timeouts/wrong results Must be called once per session immediately after get_database_schema. Contains query patterns for time-series selection, return calculations, screening joins, window functions, backtesting, and performance optimization. Time-series queries will timeout or return wrong results without these patterns. After this tool returns, call stock_data_query to execute SQL.

输入模式

{
  "type": "object",
  "properties": {}
}

输出模式

{
  "type": "object",
  "properties": {
    "result": {
      "type": "string"
    }
  },
  "required": [
    "result"
  ],
  "description": "Generic wrapper for non-object return types.",
  "x-fastmcp-wrap-result": true
}
🟢load_fundamental_workflow

Load fundamental workflow for valuation, cash flow, margins, balance sheet. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks about company valuation, "is X a good buy", financial health, debt levels, profitability ratios, revenue trends, earnings quality, or any deep-dive company analysis. Can be combined with other workflow tools.

输入模式

{
  "type": "object",
  "properties": {}
}

输出模式

{
  "type": "object",
  "properties": {
    "result": {
      "type": "string"
    }
  },
  "required": [
    "result"
  ],
  "description": "Generic wrapper for non-object return types.",
  "x-fastmcp-wrap-result": true
}
🟢load_technical_workflow

Load technical workflow for RSI, MACD, SMA, Bollinger Bands, entry/exit. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks about RSI, MACD, moving averages, Bollinger Bands, support/resistance, overbought/oversold, momentum, trend, chart patterns, golden cross, entry/exit signals, or "is X oversold/overbought". Can be combined with other workflow tools.

输入模式

{
  "type": "object",
  "properties": {}
}

输出模式

{
  "type": "object",
  "properties": {
    "result": {
      "type": "string"
    }
  },
  "required": [
    "result"
  ],
  "description": "Generic wrapper for non-object return types.",
  "x-fastmcp-wrap-result": true
}
🟢load_screening_workflow

Load screening workflow to find, filter, scan, rank stocks, top N by.... REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks to find, screen, scan, rank, or filter stocks — "find stocks that...", "top 10 by...", "best dividend stocks", value/growth screens, sector ranking, or any multi-factor selection. Can be combined with other workflow tools.

输入模式

{
  "type": "object",
  "properties": {}
}

输出模式

{
  "type": "object",
  "properties": {
    "result": {
      "type": "string"
    }
  },
  "required": [
    "result"
  ],
  "description": "Generic wrapper for non-object return types.",
  "x-fastmcp-wrap-result": true
}
🟢load_comparison_workflow

Load comparison workflow for X vs Y, peer analysis, relative valuation. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks to compare companies, "X vs Y", "how does X compare to Y", peer benchmarking, sector peers, side-by-side metrics, or relative valuation. Can be combined with other workflow tools.

输入模式

{
  "type": "object",
  "properties": {}
}

输出模式

{
  "type": "object",
  "properties": {
    "result": {
      "type": "string"
    }
  },
  "required": [
    "result"
  ],
  "description": "Generic wrapper for non-object return types.",
  "x-fastmcp-wrap-result": true
}
🟢load_earnings_workflow

Load earnings workflow for EPS surprises, beat/miss, estimates, revenue. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks about earnings results, EPS surprises, beat/miss history, "did X beat estimates", quarterly earnings, revenue growth trends, earnings season, or estimates vs actuals. Can be combined with other workflow tools.

输入模式

{
  "type": "object",
  "properties": {}
}

输出模式

{
  "type": "object",
  "properties": {
    "result": {
      "type": "string"
    }
  },
  "required": [
    "result"
  ],
  "description": "Generic wrapper for non-object return types.",
  "x-fastmcp-wrap-result": true
}
🟢load_backtesting_workflow

Load backtesting workflow for stop-loss, exit rules, Sharpe, forward returns. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks to backtest, simulate, validate a strategy, test "what happens after X", compare forward returns, measure win rates or hit rates, compute Sharpe, drawdown, profit factor, rotation strategies, basket returns, set stop-loss or trailing stop levels, test exit rules or profit targets, or any hypothetical return over past data. Can be combined with other workflow tools.

输入模式

{
  "type": "object",
  "properties": {}
}

输出模式

{
  "type": "object",
  "properties": {
    "result": {
      "type": "string"
    }
  },
  "required": [
    "result"
  ],
  "description": "Generic wrapper for non-object return types.",
  "x-fastmcp-wrap-result": true
}
🟢load_filing_workflow

Load filing workflow for SEC/EDGAR metadata, 8-K events, 10-K/10-Q reports. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL whenever the user asks about filing dates, filing activity, "who filed", "filed a form", filing frequency, SEC filings, EDGAR, 8-K events, 10-K/10-Q reports, proxy statements, or any query involving the sec_filings table (metadata - when/what type, not transaction detail). For insider transaction detail (shares, prices, cluster buying), use load_insider_workflow instead. Can be combined with other workflow tools.

输入模式

{
  "type": "object",
  "properties": {}
}

输出模式

{
  "type": "object",
  "properties": {
    "result": {
      "type": "string"
    }
  },
  "required": [
    "result"
  ],
  "description": "Generic wrapper for non-object return types.",
  "x-fastmcp-wrap-result": true
}
🟢load_insider_workflow

Load insider workflow for Form 3/4/5, insider buy/sell, cluster buy, 13D/G. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks about insider transactions, insider buying/selling, Form 3 initial holdings, Form 4/5 transactions, cluster buying, executive purchases, officer sales, 10b5-1 plans, activist stakes, 13D/G filings, beneficial ownership, "who is buying/selling", or "track this insider across companies". Can be combined with other workflow tools.

输入模式

{
  "type": "object",
  "properties": {}
}

输出模式

{
  "type": "object",
  "properties": {
    "result": {
      "type": "string"
    }
  },
  "required": [
    "result"
  ],
  "description": "Generic wrapper for non-object return types.",
  "x-fastmcp-wrap-result": true
}
🔴export_to_excel(query, title)

Export query results to a branded Shibui Finance Excel spreadsheet. Runs the same SQL query as stock_data_query but returns a downloadable Excel file instead of raw data. The spreadsheet includes branded headers, smart number formatting, and auto-fitted columns.

输入模式

{
  "type": "object",
  "properties": {
    "query": {
      "description": "The SQL query to execute and export. Same query used with stock_data_query.",
      "type": "string"
    },
    "title": {
      "description": "Title for the spreadsheet header (e.g. \"Mega-Cap Stock Comparison\").",
      "type": "string"
    }
  },
  "required": [
    "query",
    "title"
  ]
}

输出模式

{
  "type": "object",
  "properties": {
    "result": {
      "type": "string"
    }
  },
  "required": [
    "result"
  ],
  "description": "Generic wrapper for non-object return types.",
  "x-fastmcp-wrap-result": true
}

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已验证未记录版本12 个工具
已验证未记录版本12 个工具