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mcp-knowledge

by io.github.getgapup

india_market_data

Read-only

Indian capital market intelligence for the IN diaspora (30M+) and investors. Covers NSE, BSE, and MCA corporate registry across four modes:

• company — full company profile: name, CIN, exchange, NSE/BSE tickers, industry, incorporation date, paid-up capital, registered office, status, directors • market_quote — real-time quote: price (INR), change%, volume, market cap, P/E ratio. Sources: Yahoo Finance (primary), BSE API, NSE API (proxy-gated) • sector_overview — Nifty/Sensex sector snapshot: top 5 companies by market cap. Supported sectors: it, banking, pharma, energy, auto, fmcg, realestate, metals, telecom, consumer • mca_filing — Ministry of Corporate Affairs filings. Requires CIN for direct lookup.

Input formats accepted: • NSE ticker (e.g. 'RELIANCE', 'TCS.NS') • BSE 6-digit code (e.g. '500325' for Reliance) • CIN 21-char (e.g. 'L17110MH1973PLC019786') • Company name EN (e.g. 'Reliance Industries', 'Tata Consultancy') • Sector keyword (e.g. 'IT services', 'banking', 'pharma')

ENV: AICI_RESEARCH_PROXY_URL with country-in routing unlocks NSE direct API and MCA.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYesAnalysis mode.
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.
queryYesNSE/BSE ticker, CIN (21 chars), company name (EN), or sector keyword.
exchangeNoExchange filter. Default: all.

Output Schema

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

TDQS

A4.4/5.0
Behavior4/5

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

Annotations indicate readOnlyHint=true, and the description reinforces this by describing read operations. It adds behavioral context beyond annotations, such as data sources (Yahoo Finance, BSE API, NSE proxy) and async polling behavior via the 'async' parameter. No contradictions with annotations.

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 bullet points and clear sections, making it easy to scan. It is appropriately detailed without being verbose. Minor redundancy could be trimmed (e.g., listing modes twice).

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, async option, and output schema exists), the description covers all essential aspects: modes, inputs, sources, environment variable, and async behavior. It is fully self-contained for an agent to invoke correctly.

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 baseline is 3. The description adds value by explaining the mode enum in detail, giving concrete examples of query inputs, and clarifying the async parameter's behavior. This goes beyond what the schema provides.

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 Indian capital market intelligence, enumerates four distinct modes (company, market_quote, sector_overview, mca_filing), and lists accepted input formats. This distinguishes it from siblings like china_market_data and corporate_registry_lookup.

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?

The description explains when to use each mode (e.g., 'company' for full profiles, 'market_quote' for real-time quotes) and details input formats. It does not explicitly state when not to use the tool, but the context is clear. No alternative tools are mentioned for comparison.

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

C2.8/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially in competitive intelligence, ESG, and risk assessment. For example, there are multiple tools for competitor analysis (competitive_deep_dive, competitor_intel, competitor_moves, etc.) with unclear boundaries. Agents would struggle to select the correct tool without deep understanding of subtle differences.

Naming Consistency2/5

Tool names are a mix of English and French, and follow no consistent pattern. Some use snake_case (e.g., abm_architect, action_plan_esg), while others are verb-focused (e.g., content_catalog, fx_rate). The lack of a uniform naming convention makes it hard for agents to predict tool names.

Tool Count1/5

With 271 tools, the server is excessively large. Even for a broad knowledge domain, this number of tools makes discovery and selection inefficient. Typical coherent servers have 3-15 tools; this has an order of magnitude more, indicating poor scoping.

Completeness3/5

The tool set covers many domains (compliance, finance, marketing, HR, etc.), but the coverage is uneven due to redundancy. Key areas have multiple overlapping tools, while some sub-domains may still have gaps. Overall, the surface is broad but not well-curated.

Resources