Skip to main content
Glama
dragosh29

TicketSource MCP server

by dragosh29

Find customers

find_customers
Read-only

Search for customers by partial name, email, or phone. Pages through customer records to return matching profiles.

Instructions

Search customers by part of their name, email or phone number. The API has no server-side search, so this pages through the customer list (100 per call) up to max_pages.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesName, email or phone fragment
max_pagesNoPages of 100 customers to scan
max_resultsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

Beyond the readOnly/openWorld annotations, the description discloses a non-obvious implementation trait: there is no server-side search, so the tool pages through the customer list in chunks of 100 up to max_pages. This signals potential cost and limited scan depth. It does not explain how max_results interacts with paging, but annotations already cover the safety profile.

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 carry exactly the needed information: the search purpose first, then the important pagination caveat. No filler or redundant restatement of annotations.

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?

The description is mostly adequate, but max_results remains ambiguous: an agent cannot tell whether it caps returned matches after scanning or stops scanning early. Given there is no output schema, a one-sentence clarification about how max_results limits results would make the tool complete to invoke correctly.

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 67%, with query and max_pages already described. The description adds slight value by clarifying query as a name/email/phone fragment and max_pages as scanning pages of 100 customers, but it says nothing about max_results, which has no schema description. There is a clear remaining gap.

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 first sentence names a specific verb ('Search'), the resource ('customers'), and the matching rule ('by part of their name, email or phone number'). This clearly distinguishes find_customers from the exact-fetch sibling get_customer and from event/performance tools.

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 communicates when to use the tool: partial-match search over customer name, email, or phone. It also explains why pagination is necessary ('The API has no server-side search'). It does not explicitly name get_customer as the alternative for exact lookups, so it lacks full sibling routing.

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