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AKBridge MCP Server

by kevynf
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Python
Hybrid

get_qhkc_fund_position

Read-onlyIdempotent

Retrieve QHKC fund total position distribution for futures contracts within the 2016-10-10 to 2019-09-30 period. Returns pandas DataFrame with symbol, value, ratio, and long/short breakdown.

Instructions

奇货可查-资金-总持仓分布 可获取数据的时间段为："2016-10-10:2019-09-30" :param url: 网址 :param date: 中文名称 :return: 总持仓分布 :rtype: pandas.DataFrame symbol_df name value ratio date IC 1552535406 0.195622 20190924 IF 536644080 0.0676182 20190924 橡胶 536439921 0.0675924 20190924 沪铜 460851099 0.0580681 20190924 豆粕 401005794 0.0505275 20190924 螺纹钢 329159263 0.0414747 20190924 焦炭 325646968 0.0410321 20190924 燃料油 313246789 0.0394697 20190924 IH 245556750 0.0309406 20190924 棉花 214538541 0.0270323 20190924 PTA 206340552 0.0259993 20190924 白糖 139901255 0.0176278 20190924 豆油 133664010 0.0168419 20190924 沪铝 109789864 0.0138337 20190924 沪锌 107440906 0.0135378 20190924 纸浆 95517374 0.0120354 20190924 苹果 81058733 0.0102136 20190924 塑料 63665245 0.00802194 20190924 菜油 61544593 0.00775474 20190924 铁矿石 60751108 0.00765475 20190924 焦煤 58327920 0.00734943 20190924 甲醇 52148752 0.00657084 20190924 沥青 49207374 0.00620022 20190924 菜粕 48266258 0.00608164 20190924 棕榈油 31615548 0.00398362 20190924 PP 29374826 0.00370128 20190924 豆一 22368376 0.00281846 20190924 玉米 13861567 0.00174658 20190924 沪锡 7485903 0.000943238 20190924 淀粉 4811234 0.000606225 20190924 棉纱 3627240 0.000457039 20190924 尿素 2290674 0.000288629 20190924 鸡蛋 2035406 0.000256465 20190924 粳米 1999282 0.000251913 20190924 油菜籽 533482 6.72197e-05 20190924 晚籼稻 0 0 20190924 强麦 0 0 20190924 沪铅 89914 1.13293e-05 20190924 豆二 379200 4.77799e-05 20190924 硅铁 5025872 0.000633269 20190924 红枣 8521668 0.00107375 20190924 锰硅 9472832 0.00119359 20190924 郑煤 9888272 0.00124594 20190924 乙二醇 18324242 0.00230889 20190924 PVC 19454830 0.00245135 20190924 玻璃 27076226 0.00341166 20190924 热卷 28832929 0.003633 20190924 沪银 375076371 0.0472603 20190924 沪镍 411622624 0.0518652 20190924 沪金 719371823 0.0906422 20190924

long_short_df name value ratio date 空 6303252093 0.794222 20190924 多 1633136803 0.205778 20190924

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNohttps://qhkch.com/ajax/fund_position_pie.php
dateNo20190924

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

B3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly/idempotent/non-destructive), and the description adds real behavioral context: the temporal bound of the dataset and the shape of the return (a per-symbol position table plus a long/short aggregate). The stale 2019 sample is a weakness, but the output-format disclosure is genuinely useful since no output schema exists.

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

Conciseness2/5

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

Purpose and time range are front-loaded, but the body is dominated by a 50-row raw data dump of stale example values that consumes most of the text without adding reusable guidance. This is excessive and poorly structured for an agent-facing definition.

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

Completeness3/5

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

With no output schema, describing the return is important and the description does show the two-table structure, plus it states the usable date range. But it omits usable parameter semantics (and mislabels date) and gives no routing guidance against numerous sibling tools, leaving clear gaps.

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

Parameters2/5

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

Schema description coverage is 0%, so the description carries the full burden, yet it only offers a trivial gloss for url (网址) and a misleading one for date (中文名称 = 'Chinese name'), when the parameter's default '20190924' makes clear it is a date. The misleading label actively harms correct invocation rather than aiding it.

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 names a specific resource (奇货可查 fund total position distribution / 总持仓分布) and its example output shows futures symbol position values and long/short breakdowns, so an agent can identify what data comes back. However it does not distinguish itself from close siblings like get_qhkc_fund_bs or get_qhkc_fund_money_change, so the boundary between this and other qhkc fund tools is left implicit.

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 only guidance is the data-availability window (2016-10-10 to 2019-09-30), which tells the agent the effective range but nothing about when to choose this tool over alternatives. There is no mention of when-not-to-use or which sibling covers a related need.

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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