Skip to main content
Glama
Sign In
apollo-io-mcp

apollo-io-mcp

by thevgergroup
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Bulk Enrich People

apollo_bulk_enrich_people

Enrich multiple people in bulk with Apollo match by supplying an array of emails, LinkedIn URLs, names, or companies. Optionally reveal phone numbers and personal emails.

Instructions

Bulk enrich multiple people using Apollo match. Provide an array of people with email, linkedin_url, name, or company.

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": {
      "people": "<people>"
    },
    "name": "apollo_bulk_enrich_people"
  }
}

Input Schema

NameRequiredDescriptionDefault
peopleYes
reveal_phone_numberNoReveal phone numbers (default: false)
reveal_personal_emailsNoReveal personal emails (default: false)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv3.0.0
    • changedInput schema / properties / people / items / properties / email / pattern
      Previous value: -"^(?!\\.)(?!.*\\.\\.)([A-Za-z0-9_'+\\-\\.]*)[A-Za-z0-9_+-]@([A-Za-z0-9][A-Za-z0-9\\-]*\\.)+[A-Za-z]{2,}$"New value: +"^(?:[A-Za-z0-9_'+\\-]+\\.)*[A-Za-z0-9_'+\\-]*[A-Za-z0-9_+-]@(?:[A-Za-z0-9][A-Za-z0-9\\-]*\\.)+[A-Za-z]{2,}$"
  2. First observedv2.2.1

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden and mostly fails it. It says enrichment happens "using Apollo match" and what inputs to supply, but discloses nothing about credit consumption, whether reveal_phone_number/reveal_personal_emails incur extra cost, match-rate limitations, partial-match handling, or mutation side effects.

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 short sentences, front-loaded with the action and scope followed by the input requirement. No filler, no repetition of the title, nothing that fails to earn its place.

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

Completeness2/5

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

For a batch operation with no annotations and no output schema, key information is absent: response shape per record, behavior on unmatched entries, credit costs, batch size limits, and rate limits. An agent can construct the call but cannot predict its cost or outcome.

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 67%, and the description fills the most important gap: the people array and its accepted identifier fields (email, linkedin_url, name, company) are undocumented in the schema but spelled out here. The two reveal_* booleans are already described in the schema, so the description neither adds nor repeats value for them.

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 states a specific verb+resource ("Bulk enrich multiple people") and names the mechanism ("Apollo match"), which lets an agent distinguish it from the single-record sibling apollo_enrich_person by the word "bulk" / "multiple". It stops short of explicitly naming the sibling it replaces, so it is clear but not fully self-differentiating.

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?

Bulk framing implies the usage context (multiple records at once vs. the single-person enrich tool), but there is no explicit when/when-not statement, no mention of alternatives, and no prerequisites or credit-cost warnings. Usage must be inferred from the word "bulk".

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

Deploy Server

Other Tools