INDUSS Research Intelligence MCP Server

company_overview

Read-only

Generate a narrative business overview for any company, covering products, services, and target market, using data from the company's website and LinkedIn.

Instructions

Produces a narrative business overview (what the company does, products/services, target market) sourced from the company's own site and LinkedIn.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "context": "<context>"
    },
    "name": "company_overview"
  }
}

Input Schema

Name	Required	Description	Default
`context`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 1, 2026

TDQS

B3/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the agent knows it is a safe read operation. The description adds value by specifying data sources (company site, LinkedIn) and output type (narrative overview), but it does not disclose limitations, error behavior, or data freshness details.

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 a single, focused sentence that immediately states the tool's purpose and includes relevant details about content and sources. No filler or repetition.

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

Completeness2/5

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

Despite being concise, the description is incomplete for a research tool with one complex parameter and many sibling tools. It lacks usage differentiation, parameter explanations, and details on output structure or failure modes.

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?

The schema has a single nested 'context' object with properties like company, country, listed, sector, and companyDomain, but schema_description_coverage is 0% and the tool description does not explain these fields or their semantics. It only implies the company is the subject, leaving other parameters ambiguous.

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 uses a specific verb ('Produces') and resource ('narrative business overview') and clarifies content (what the company does, products/services, target market) and sources (company site, LinkedIn). However, it does not explicitly distinguish this from sibling tools like 'company_profile', which may overlap.

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 description provides no guidance on when to use this tool versus alternatives such as 'company_profile', 'industry_overview', or 'search_company'. It simply states what it does, leaving the AI agent to infer appropriate usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server