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dyngai

apollo-mcp

by dyngai

apollo_search_companies

Search for companies in Apollo using filters for location, industry, size, and revenue to target specific organizations.

Instructions

Search for companies/organizations in Apollo with comprehensive filtering options. Use filters to target specific company types, locations, sizes, and industries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number (default: 1)
queryNoSearch query for company names, industries, or keywords
filtersNoAdvanced filtering options. Start with location + keywords for best results.
per_pageNoResults per page (1-100, default: 25). Apollo rejects anything above 100 with HTTP 422.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description must fully disclose behavior. It only mentions 'comprehensive filtering options' but does not discuss pagination, rate limits, error handling, or what happens with invalid inputs. This is insufficient for safe invocation.

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 concise sentences. Every word adds value, and it is front-loaded with the main purpose. No wasted information.

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?

Given the moderate complexity (4 parameters, output schema exists), the description is adequate but not fully complete. It lacks mention of pagination limits (though schema covers per_page) or typical use cases, but the high schema coverage compensates.

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?

The input schema has 100% description coverage, so each parameter is already documented. The description adds a general usage hint ('target specific company types...') but no new semantic value beyond what the schema provides. Baseline 3 is appropriate.

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 clearly states the action ('Search') and resource ('companies/organizations'), which is specific. However, it does not explicitly differentiate from sibling search tools like apollo_search_people or apollo_search_contacts, though the name makes the target clear.

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 usage ('Use filters to target...') but does not specify when to use this tool versus alternatives, or provide exclusion criteria. The guidance is minimal and leaves the agent to infer context.

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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