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bigl34

inFlow Inventory MCP Server

by bigl34

list_customers

Search and list customers from inFlow Inventory with optional filters for name, email, phone, active status, location, and more. Sort, paginate, and include related data for targeted customer lookups.

Instructions

Search and list customers with optional filtering

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoFilter by customer name (partial match)
skipNoNumber of records to skip
sortNoProperty to sort by (e.g., name, modifiedDate)
countNoNumber of records to return (max 100)
emailNoFilter by email
phoneNoFilter by phone
smartNoSmart search across customer fields (name, email, phone)
includeNoRelated data to include (e.g., contacts, pricingScheme, paymentTerms)
isActiveNoFilter by active status
sortDescNoSort in descending order
locationIdNoFilter by location ID
includeCountNoInclude total record count in response
pricingSchemeIdNoFilter by pricing scheme ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.4.0-alpha.2

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden and fails to. It is a 13-parameter read tool with no mention of pagination behavior, the max-100 cap on results, default page size, or authentication/permission needs — all of which are things an agent calling it would need before invoking.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no filler. It is not bloated, though one sentence is arguably too thin for a 13-parameter tool (that under-specification is captured under contextual completeness rather than conciseness).

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 tool with 13 parameters, no annotations, and no output schema, the one-line description is under-specified. It omits return shape, pagination/skip-count interaction, sorting defaults, and the meaning of 'smart' vs specific-field filters, leaving gaps that neither annotations nor an output schema fill.

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 description coverage is 100%, so every parameter (name, skip, sort, count, smart, include, etc.) is already documented in the schema. The description adds only the generic claim of 'optional filtering', which does not extend meaning beyond the schema, so the baseline 3 applies.

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?

States a specific verb ('list') and resource ('customers') with the search/filter scope. However, it does nothing to distinguish itself from siblings like get_customer or the analogous list_vendors, so an agent gets no routing help beyond the name itself.

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

Usage Guidelines2/5

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

The phrase 'with optional filtering' only implies that filters exist; it gives no when-to-use guidance, no indication of when to prefer get_customer (single record) over this bulk list, and no exclusions or prerequisites. No alternative tools are named.

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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