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rajyash205

INDUSS Research Intelligence MCP Server

by rajyash205

generate_institutional_report

Generate a complete institutional research report in one call: company profile, financials, macro/industry, competitors, funding, risk screens, and news—rendered as JSON, Markdown, HTML, or PDF.

Instructions

Generates a complete institutional research report for a company in one call: company profile, financial snapshot, macro/industry overview (runs even without a sector — falls back to the company's own industry), a server-ranked competitor list, funding history, a combined litigation/promoter/adverse-media risk screen (with an evidence checklist of exactly which sources were checked), and recent news — composed into report sections and rendered in the requested output formats (json/markdown/html/pdf). Use this instead of calling search_company, company_profile, financial_statements, discover_competitors, litigation_history, promoter_background, negative_news, latest_news, and generate_pdf separately. The report's closing section tells you (the calling model) exactly which analyst-judgment sections to add next — SWOT, bull/bear case, valuation — each written in your own analytical voice and marked metadata.kind = "ai_interpretation" (see generate_report), so the finished document reads like an analyst's note rather than a data dump. Write plainly and directly: state the number and its implication in one motion ("EBITDA margin expanded 420bp to 34% on operating leverage"), not hedged narration ("the data appears to suggest a possible improvement") — every one of the reference institutional notes this convention was modeled on (PL Capital, ICICI Securities, Motilal Oswal) writes this way.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
listedNounknown
sectorNoIndustry/sector — sharpens the macro/Industry Overview section's search; if omitted, that section falls back to searching around the company's own industry instead of being skipped
companyYesCompany (or promoter/legal entity) name to research
countryNoindia
reportTypeNogeneral_diligence
companyDomainNoCompany's own website domain, e.g. acme.com
outputFormatsNoWhich rendered formats to include in the response

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

Discloses behaviors like sector fallback, server-ranked competitor list, evidence checklist, and that the closing section directs the caller to add analyst-judgment sections. However, it includes extensive style guidance that is more about the calling model than the tool's own behavior.

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

Conciseness1/5

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

The description is a single, extremely long, repetitive sentence. It includes redundant meta-commentary about writing style and reference institutions, making it poorly structured and not concise.

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?

Provides a detailed overview of report contents and which sibling tools it replaces, but includes extraneous writing-style instructions that could confuse an agent. Lacks any mention of error handling or response structure, though no output schema is expected.

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

Parameters3/5

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

Only the sector parameter receives extra context via the fallback note, aligning with the schema description. Other parameters (listed, country, reportType) are not additionally explained, and schema coverage is moderate at 57%.

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 the tool generates a complete institutional research report in one call, listing the specific components. It also explicitly distinguishes itself from sibling tools by instructing to use this instead of calling them separately.

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

Usage Guidelines5/5

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

It explicitly says 'Use this instead of calling ... separately', giving clear when-to-use guidance relative to alternatives. The fallback behavior for sector omission is also described.

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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