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gapup-mcp

by io.github.getgapup

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
NameRequiredDescriptionDefault
modeYesAnalysis mode. company=full profile, market_quote=price data, sector_overview=top 5 by sector, regulatory_filing=recent filings.
asyncNoIf 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.
queryYesTicker (6-digit A-share, 4-digit HK, Yahoo format), company name (ZH or EN), or sector keyword.
exchangeNoExchange filter. Default: all. Affects sector_overview ticker selection.
period_daysNoLookback period in days for regulatory filings. Default: 30.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYes
queryYes
statusYes
companyNo
sourcesYes
market_quoteNo
quality_scoreYes
sector_overviewNo
regulatory_filingsNo

TDQS

A4.5/5.0
Behavior4/5

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

Beyond the annotations (readOnlyHint=true, destructiveHint=false), the description discloses important behavioral details: data sources (Yahoo Finance always accessible, Eastmoney/HKEX with proxy), and the note that Eastmoney/CSRC/SSE are blocked from datacenter IPs without AICI_RESEARCH_PROXY_URL. It also describes per-mode return contents, which is useful context.

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

Conciseness5/5

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

The description is well-structured and efficient: a brief introductory sentence, bullet-pointed mode definitions, input format list, and data source note. Every section earns its place, and the length is justified by the tool's four-mode complexity. No fluff or redundancy.

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 (four modes, multiple input formats, 5 parameters), the description covers all necessary operational context: modes with output fields, accepted ticker/name/sector formats, data source behaviors, and proxy configuration. With an output schema present, return values need no further explanation. The async parameter is covered by schema descriptions, so this is sufficiently complete.

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 description coverage is 100%, so the baseline is 3. The description adds significant value by listing accepted input formats with concrete examples (e.g., '600519' for Moutai SSE, '0700.HK' for Tencent, '腾讯'), detailing sector keywords, and explaining the period_days lookback. This enriches the query and sector_overview parameters beyond schema descriptions.

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 a specific verb+resource: 'Chinese capital market intelligence' covering A-Shares, H-Shares, and ADRs across four distinct modes. It distinguishes itself from neighboring tools like india_market_data through explicit geographic scope and enumerates the exact output for each mode.

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

Usage Guidelines4/5

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

Provides clear context on when to use the tool by enumerating supported markets and input formats. It also gives operational guidance on data source availability and the proxy requirement for full coverage. However, it does not explicitly name alternatives or state when not to use this tool (e.g., for Indian markets).

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

C2.4/5.0
Disambiguation1/5

Over 50 tools share the identical template 'Gapup agent-payable C-suite expertise' with similar French descriptions and reference cases, making their boundaries indistinguishable. Clusters like competitor_intel, competitive_deep_dive, competitor_moves, competitor_profiles, competitor_pricing_radar, competitor_pricing_scrape, and competitor_recommendations heavily overlap in purpose.

Naming Consistency1/5

Names are chaotic: mix of French and English, snake_case and camelCase, verb_noun, noun, and adjective forms with no uniform pattern. Examples like 'bp_narratif', 'content_enrichment', 'ai_governance_full_report_async', and 'job_result' show no coherent naming convention.

Tool Count1/5

271 tools is far beyond any reasonable MCP server scope, creating an overwhelming selection burden for agents. This count vastly exceeds the 25+ threshold for 'too many' and makes navigation impractical.

Completeness2/5

While the server covers many business domains, it lacks lifecycle operations (e.g., no update/delete tools for the deliverables it generates) and the input specifications are vague ('documented case fields' without documentation), creating functional dead ends. The sheer breadth does not compensate for these gaps.

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