gapup-mcp

china_market_data

Read-only

Chinese capital market intelligence for the ZH diaspora (50M+) and institutional investors. Covers A-Shares (SSE/SZSE), H-Shares (HKEX), and ADRs across four modes:

• company — full company profile: name ZH/EN, USCC (18-digit social credit code), exchange, industry (CSRC classification), chairperson, registered capital, SOE flag • market_quote — real-time quote: price (CNY or HKD), change%, volume, market cap, P/E ratio, dividend yield, last update timestamp • sector_overview — sector snapshot: top 5 companies by market cap, avg P/E, 30-day sector index change. Supported sectors: semiconductor, ev, battery, technology, finance, energy, realestate, consumer, pharma, telecom • regulatory_filing — recent regulatory disclosures (HKEX filings: annual, quarterly, announcements, mergers, IPOs) with title, date, document URL

Input formats accepted: • 6-digit A-Share ticker (e.g. '600519' for Moutai SSE) • HKEX ticker (e.g. '0700.HK' or '700' for Tencent) • Company name in EN or ZH (e.g. '腾讯', 'Kweichow Moutai') • Sector keyword (e.g. 'semiconductor', '半导体')

Data sources: Yahoo Finance (primary, always accessible), Eastmoney push2 + CompanySurvey (via Bright Data proxy when AICI_RESEARCH_PROXY_URL is set), HKEX filing API. Note: Eastmoney/CSRC/SSE are blocked from datacenter IPs without proxy — set AICI_RESEARCH_PROXY_URL to unlock full coverage.

Input Schema

TableJSON Schema

Name	Required	Description
`mode`	Yes	Analysis mode. company=full profile, market_quote=price data, sector_overview=top 5 by sector, regulatory_filing=recent filings.
`async`	No	If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
`query`	Yes	Ticker (6-digit A-share, 4-digit HK, Yahoo format), company name (ZH or EN), or sector keyword.
`exchange`	No	Exchange filter. Default: all. Affects sector_overview ticker selection.
`period_days`	No	Lookback period in days for regulatory filings. Default: 30.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`mode`	Yes
`query`	Yes
`status`	Yes
`company`	No
`sources`	Yes
`market_quote`	No
`quality_score`	Yes
`sector_overview`	No
`regulatory_filings`	No

TDQS

A4.4/5.0

Behavior5/5

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

The description adds significant behavioral context beyond annotations: it details data sources (Yahoo Finance, Eastmoney, HKEX), proxy requirements for full coverage, and the asynchronous polling mechanism via job_result. No contradiction with annotations (readOnlyHint=true, destructiveHint=false) is present.

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 well-structured with sections and bullet points, making complex information scannable. It is slightly verbose but every sentence adds clarity given the tool's breadth. No redundancy is present, earning a high score for its informational density.

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

Completeness5/5

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

Given the tool's complexity (5 parameters, 2 required, 2 enums, output schema exists), the description covers all essential aspects: modes, input formats, data sources, proxy requirements, and the async flow. It is complete without needing to describe return values, as the output schema handles that.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds value by elaborating on the modes (e.g., 'company — full company profile...'), clarifying input formats (ticker, name, sector), and explaining the async parameter’s purpose. This extra context raises the score above baseline.

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

Purpose5/5

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

The description clearly states it provides Chinese capital market intelligence, covering A-Shares, H-Shares, and ADRs across four distinct modes (company, market_quote, sector_overview, regulatory_filing). Each mode is briefly defined with specific output details, making the tool's purpose highly specific and distinguishable from siblings like india_market_data or historical_price_series.

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

Usage Guidelines3/5

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

The description implies when to use the tool (for Chinese market data) but does not explicitly state when not to use it or name alternative tools. It lacks explicit guidance on distinguishing from similar tools (e.g., india_market_data, realtime_data_streams), leaving the agent to infer usage boundaries.

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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TDQS

C2.5/5.0

Disambiguation2/5

With 271 tools, many have overlapping purposes (e.g., multiple competitor intel tools, multiple financial modelers, multiple ESG auditors). Detailed descriptions help slightly, but the sheer volume creates confusion. Agents would struggle to select the right tool among many similar options.

Naming Consistency1/5

Tool names are wildly inconsistent: mix of English and French, snake_case and short phrases, some very generic (process, run, execute equivalents). No discernible naming convention (e.g., abm_architect vs. boundary_control vs. bp_narratif). This makes it hard to predict tool names.

Tool Count1/5

271 tools is far beyond typical well-scoped servers (3-15). This indicates an unfocused, over-bloated tool surface. Even for a general business intelligence server, this number is excessive and violates the principle of each tool earning its place.

Completeness2/5

Despite the large count, coverage feels scattered. Some domains (e.g., content, competitive intel) have many tools, while others (e.g., supply chain, HR) have gaps. The set lacks a coherent scope; it seems like a dump of many separate tool collections rather than a complete, curated surface.

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