QuickBooks Desktop MCP

Overview Schema Source Related Servers Discussions Admin

qb_vendor_history

Read-only

Retrieve the accounts a vendor's past transactions were booked to, with counts, so you can choose a proven account for new transactions instead of guessing.

Instructions

Returns which account(s) this vendor's past transactions were booked to, with counts -- e.g. {"Food Purchases": 175}. Use this before guessing an account for a new transaction from a known vendor: prefer whatever this vendor has actually been booked to before, not a plausible-sounding guess.

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": {
      "vendor_name": "<vendor_name>"
    },
    "name": "qb_vendor_history"
  }
}

Input Schema

Name	Required	Description	Default
`txn_types`	No
`vendor_name`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Nov 1, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds real value beyond that by showing the return shape as a frequency map (e.g., {"Food Purchases": 175}) and framing it as evidence rather than an authoritative mapping. It stops short of saying how far back the history reaches or whether results are capped.

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 short sentences, front-loaded with the return shape, then the workflow rationale. Every sentence contributes: what it returns, an example, and why to call it.

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?

No output schema exists, and the description compensates by illustrating the response format directly. Combined with read-only annotations, this is nearly sufficient for a two-parameter lookup, with the only real hole being undocumented txn_types semantics and no note on history depth.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the full burden, yet it only implies vendor_name and never mentions the txn_types filter at all. An agent reading this has no way to know a txn_types array exists semantically, what values it accepts, or what happens when it is null.

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?

States a specific verb and resource: returns the accounts a vendor's past transactions were booked to, with counts, plus a concrete output example. This is clearly distinguishable from siblings like qb_query_transactions or qb_list_vendors.

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?

Gives an explicit trigger: call this before guessing an account for a new transaction from a known vendor, and prefer observed history over a plausible guess. It doesn't name a sibling alternative (e.g., raw transaction querying) for cases where history is absent, but the intended moment of use is unambiguous.

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