Skip to main content
Glama
kooperativa-team

@kooperativa_team/mcp-server

Official

Kooperativa: search companies

kooperativa_search_companies

Find companies in Kooperativa's data lake by name, HQ location, industry, and employee count. Combine optional filters to narrow B2B prospects.

Instructions

Search the Kooperativa data lake of companies by name, HQ location, industry, and headcount range. All filters are optional and combine with AND logic, but at least one filter is required. min_staff/max_staff are both inclusive and either can be omitted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoHQ city name.
pageNo
queryNoFull-text search across company name and tagline.
countryNoHQ country code, ISO 2-letter, e.g. 'US'. Full names return 0 results.
industryNoExact industry label using the company taxonomy (differs from /people/search industry values), e.g. 'Software Development'.
per_pageNo
max_staffNoMaximum employee count, inclusive.
min_staffNoMinimum employee count, inclusive.

Schema Changelog

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

  1. First observedv0.1.2

TDQS

A3.9/5.0
Behavior4/5

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

Since no annotations are provided, the description carries the behavioral disclosure burden. It discloses non-obvious behavior: at least one filter is required, filters use AND logic, min_staff/max_staff are inclusive, and either staff bound can be omitted. It does not describe response shape or pagination behavior, but the tool is read-only by nature and schema covers pagination defaults.

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 two tight sentences with no filler. It front-loads the action and resource, then immediately lists the key constraints. Every sentence adds value.

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

Completeness4/5

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

The description covers the most important non-schema requirements: at least one filter, AND logic, and inclusive staff bounds. A note about result/pagination behavior would be helpful since there is no output schema, but the schema's defaults and the tool's clear search purpose make the description sufficient for correct invocation.

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 coverage is 75%, so the baseline is 3. The description adds meaningful cross-parameter semantics beyond individual property descriptions: filters combine with AND, at least one filter is required, and min_staff/max_staff inclusivity with optional omission. This helps the agent construct valid requests.

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?

Description clearly states a specific verb and resource: 'Search the Kooperativa data lake of companies' with the key filters (name, HQ location, industry, headcount range). It does not explicitly name or exclude sibling tools like kooperativa_search_people, so sibling differentiation is implied rather than stated.

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 gives clear operational context: filters are optional individually, combine with AND, and at least one is required. However, it does not say when to prefer this tool over sibling alternatives such as kooperativa_search_people, kooperativa_enrich_company, or kooperativa_check_company.

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

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/kooperativa-team/kooperativa-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server