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viraj43

INDUSS Research Intelligence MCP Server

by viraj43

funding_history

Read-only

Retrieves a company's funding history from business databases, identifying rounds, investors, and valuation mentions with extracted facts.

Instructions

Searches Crunchbase, Tofler, MCA, Pitchbook, Dealroom, and OpenCorporates for a company's funding rounds, investors, and valuation mentions, and extracts candidate round/amount facts from the retrieved text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextYes

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

Beyond the readOnlyHint and openWorldHint annotations, the description reveals that the tool searches multiple external sources and 'extracts candidate round/amount facts from retrieved text,' signaling possible noise and text-derived inferences. It does not mention rate limits, pagination, or failure behavior, but the annotations already cover the safety profile.

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?

One dense sentence front-loads the action and then efficiently lists sources and target data. Every word earns its place, with no filler or repetition.

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?

The description covers the core behavior and output type but omits how optional context fields affect the search and what the exact return format is. Given the absence of an output schema and the range of parameters, this is a clear gap.

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?

Schema description coverage is 0%, and the description provides no guidance on the required 'company' field or the optional 'date', 'country', 'listed', 'sector', and 'companyDomain' fields. The named data sources hint at country relevance (e.g., Tofler/MCA for India), but the relationship is left implicit.

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 uses the specific verb 'Searches' and identifies the exact resource: funding rounds, investors, and valuation mentions across six named sources. It clearly distinguishes funding_history from sibling tools like financial_statements or company_overview, and the extraction phrase clarifies the output type.

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 this tool is for retrieving a company's funding history, but it never explicitly states when to prefer it over sibling research tools or which contexts it is unsuitable for. No alternatives or exclusions are mentioned, leaving the agent to infer usage from the behavior.

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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