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dyngai

apollo-mcp

by dyngai

apollo_bulk_create_contacts

Bulk create up to 100 CRM contacts per call. Provide contact details including first name, last name, email, and optional fields; returns both created and existing contacts.

Instructions

Bulk-create CRM contacts (up to 100 per call). Pass 'contacts' as a list of dicts with first_name/last_name/email and any other fields (title, organization_name, linkedin_url, contact_stage_id, owner_id, phone_numbers, etc.). Apollo returns created_contacts and existing_contacts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contactsYesList of contact dicts to create
run_dedupeNo
append_label_namesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the return behavior (created_contacts and existing_contacts) and the batch limit of 100. However, it does not mention authentication needs, rate limits, or side effects like deduplication.

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?

Two sentences with efficient front-loading of purpose and limit. Every sentence adds value with no repetition of schema fields.

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?

With 3 parameters, no annotations, and an existing output schema, the description covers purpose, limit, and output fields. Missing context includes error handling, authentication, and usage guidance versus sibling tools.

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?

Schema coverage is low (33%) – only 'contacts' has a minimal description. The description adds valuable detail for 'contacts' (list of dicts with required and optional fields) but provides no explanation for 'run_dedupe' or 'append_label_names'. For the coverage gap, the description only partially compensates.

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 action ('bulk-create'), the resource ('CRM contacts'), and a key constraint ('up to 100 per call'). This distinguishes it from single-contact creation (apollo_create_contact) and matching (apollo_bulk_match_contacts).

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 for bulk contact creation but does not explicitly state when to use this tool versus alternatives (e.g., single create). No exclusions or prerequisites are mentioned.

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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