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A1-x-Tech

A1 Google Contacts MCP

Get many contacts at once

batch_get_contacts
Read-onlyIdempotent

Retrieve up to 200 contacts at once with per-entry status and original ordering. Avoids quota-heavy individual lookups and handles missing contacts gracefully without failing the whole batch.

Instructions

Fetches up to 200 contacts in one call (People API people:batchGet) — far cheaper against the tight per-user quota than a get_contact loop. Returns responses[], one per requested resource name IN THE SAME ORDER, each { requestedResourceName, status, person }; a missing contact gets a NOT_FOUND status in its own entry instead of failing the whole call, so check per-entry status. person_fields works exactly like in get_contact.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
person_fieldsNoPerson fields to return (default names, emailAddresses, phoneNumbers, organizations, memberships). Only masked fields come back — an absent field may be unmasked, not empty.
resource_namesYesThe contacts to fetch (1..200 people/<id> resource names).
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses ordering guarantees, per-entry response shape, NOT_FOUND handling instead of whole-call failure, and the requirement to check per-entry status. This is exactly the operational detail an agent needs.

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?

Three dense sentences deliver the core behavior, quota rationale, response format, and per-entry error handling without filler. The most decision-relevant information is front-loaded.

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

Completeness5/5

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

With no output schema present, the description supplies a complete mental model of the return value, error semantics, ordering, and field behavior. An agent can invoke it confidently without inspecting other tools.

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 already 100%, and the description adds useful parametric context: person_fields behaves exactly as in get_contact and responses are returned in the same order as requested resource_names. These are meaningful additions beyond the schema's field 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 names a specific verb and resource ('Fetches up to 200 contacts in one call'), identifies the underlying People API operation, and clearly distinguishes batch_get_contacts from the get_contact loop. The title and description together make its scope obvious.

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

Usage Guidelines5/5

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

It explicitly frames the tool as the cheaper alternative to a get_contact loop under tight per-user quota, giving an agent a clear selection rule for batch retrieval. The comparison to get_contact is the needed routing guidance relative to siblings.

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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