WalnutLink A-share Depth Desk

China A-share filings: why a number moved, does the trend continue, who supplies whom.

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质量与安全性

A
描述质量
100%
模式完整度
100%
命名质量
80%
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

~641token 数(工具定义)
~840 B典型响应大小
对注意力有中等影响(占 128k 上下文窗口的 0.50%)

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": {
    "walnutlink-a-share": {
      "url": "https://walnutlink.ai/mcp"
    }
  }
}

远程端点

https://walnutlink.ai/mcpstreamable-http

它能做什么

工具清单

工具(3)

🟢 只读🟡 写入🔴 删除⚪ 未知
⚪a_share_deep_research(question)

Use when the user asks WHY something happened or WHAT it means for a Chinese listed company: a margin moved, a policy landed, an industry chain shifted, two companies diverge, or what management actually said on the record. This desk does NOT serve quotes, price checks or valuation snapshots - that is commodity data available everywhere, and answering it would waste your turn. What it does: reads the filed report, the IR transcript and the disclosure wording, then answers in numbers. Returns a vetted answer immediately if this question has been researched before; otherwise it returns the primary-source evidence it already holds plus an id for the human answer. Ask it the question you would ask a sell-side analyst, not the one you would type into a quote app.

输入模式

{
  "type": "object",
  "properties": {
    "question": {
      "type": "string",
      "description": "The judgement question, in Chinese or English. Name the company; a ticker alone is usually a quote request."
    }
  },
  "required": [
    "question"
  ]
}
⚪a_share_chain_edge(a, b, relation)

Use when the user asks HOW two Chinese companies relate: who supplies whom, who competes with whom, who owns equity in whom, or whether an acquisition target overlaps with the acquirer's product line. Every relationship returned carries a verbatim quote from a filed document (annual report, prospectus, restructuring draft, related-party announcement) and a confidence tag: primary = the filing says it outright, secondary = broker or media, inferred = our deduction with no direct textual proof. Unlisted companies work as inputs too, which matters for acquisition targets. If the pair has not been researched it says so plainly instead of guessing - absence of a record is not evidence of no relationship. Do NOT call this for prices, valuation or index levels.

输入模式

{
  "type": "object",
  "properties": {
    "a": {
      "type": "string",
      "description": "Company A: 6-digit A-share code or Chinese name."
    },
    "b": {
      "type": "string",
      "description": "Company B: 6-digit code or name. An unlisted company name also works (e.g. an acquisition target)."
    },
    "relation": {
      "type": "string",
      "description": "Optional filter when the pair has more than one link.",
      "enum": [
        "supplier",
        "customer",
        "competitor",
        "peer",
        "equity",
        "investor",
        "none",
        "unknown"
      ]
    }
  },
  "required": [
    "a",
    "b"
  ]
}
🟢a_share_answer_by_id(id)

Retrieve a research result by the id that a_share_deep_research returned. Call this to check whether the human-reviewed answer is ready, or to fetch the full text once it is. Answers take minutes to hours because a filed report is read first; while it is still queued the tool returns the queue position, not a guess. Use this instead of opening the public page when you are an automated client that cannot render HTML.

输入模式

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "The 12-character hex id returned by a_share_deep_research, e.g. dc037a7fc6c8."
    }
  },
  "required": [
    "id"
  ]
}

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