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apollo-mcp

apollo-mcp

by dyngai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

apollo_bulk_match_contacts

Match multiple CRM contacts by providing identifiers like email, LinkedIn URL, or name and organization. Resolve and enrich contacts in Apollo.io.

Instructions

Bulk-match CRM contacts. Pass 'details' as a list of dicts with email/linkedin_url/name+org. RATE LIMIT: 100/hour, 20/minute.

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": {
      "details": "<details>"
    },
    "name": "apollo_bulk_match_contacts"
  }
}

Input Schema

NameRequiredDescriptionDefault
detailsYesList of contact-identifier dicts to match

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the burden. It explicitly states rate limits (100/hour, 20/minute), which is a key behavioral constraint. It does not mention whether the operation is read-only or modifies data, but 'match' typically implies non-destructive lookup.

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, concise and front-loaded with the primary purpose. Every clause provides essential information: purpose, input format, and rate limits. No unnecessary words.

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 purpose, input format, and rate limits adequately. An output schema is present (not shown), so details on return values are not required. Minor gap: it does not clarify whether unmatched contacts are handled, but the output schema likely addresses that.

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?

The schema describes the 'details' parameter as a list of contact-identifier dicts (100% coverage). The description adds value by specifying the fields to include: email/linkedin_url/name+org, which are not present in the schema's property descriptions.

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 'Bulk-match CRM contacts' clearly states the verb (match) and resource (contacts), with 'bulk' distinguishing it from the singular sibling apollo_match_contact. This is specific and non-tautological.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies it should be used for matching multiple contacts at once, differentiating from singular alternatives. However, it does not explicitly state when not to use it or list alternative tools for specific scenarios.

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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