qb_get_customerRetrieve a customer's complete profile including contact info, email, phone, and account balance by customer ID.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | QuickBooks Customer ID |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -nullNew value: +{
+ "oneOf": [
+ {
+ "properties": {
+ "error": {
+ "description": "Error code if connection not configured",
+ "type": "string"
+ },
+ "message": {
+ "description": "Error message with setup instructions",
+ "type": "string"
+ }
+ },
+ "required": [
+ "error",
+ "message"
+ ],
+ "type": "object"
+ },
+ {
+ "properties": {
+ "Customer": {
+ "description": "Customer profile with contact info, email, phone, and balance",
+ "properties": {
+ "DisplayName": {
+ "description": "Customer display name",
+ "type": "string"
+ },
+ "Id": {
+ "description": "Customer ID",
+ "type": "string"
+ },
+ "PrimaryEmailAddr": {
+ "properties": {
+ "Address": {
+ "description": "Email address",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "PrimaryPhone": {
+ "properties": {
+ "FreeFormNumber": {
+ "description": "Phone number",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ }
+ },
+ "type": "object"
+ }
+ },
+ "type": "object"
+ }
+ ],
+ "type": "object"
+}Input schema / examplesAdded value: +[
+ {
+ "id": "1"
+ },
+ {
+ "id": "42"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds value by specifying the exact data fields returned (contact info, email, phone, account balance) and the retrieval method (by customer ID), providing context beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that conveys all essential information without any fluff. Every word serves a purpose, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and simple parameter, the description covers all needed context: what the tool does, what it includes, and how to call it. No gaps for a read-only retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'id' is fully described in the schema as 'QuickBooks Customer ID'. The tool description only echoes 'by customer ID', adding no new semantics. With 100% schema description coverage, the description adds minimal value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a customer's complete profile with specific fields (contact info, email, phone, account balance) by customer ID. This distinguishes it from sibling tools like qb_get_invoice or qb_list_invoices, which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a full customer profile is needed by ID, but does not explicitly state when to use this tool versus alternatives like qb_query or qb_list_accounts. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools are near-duplicates (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded), and there are overlapping clusters among the polymarket_* tools, research tools (deep_research, entity_profile, compare_entities, recent_changes), and AI-visibility tools (ai_visibility_check vs scan_competitor_ai_presence). The detailed descriptions help, but an agent selecting among these could easily pick the wrong one.
Snake_case is used consistently, but the naming pattern is otherwise mixed: some tools are verb_noun (validate_claim, suggest_questions), some are bare nouns (entity_profile, polymarket_edges), some are verbs without objects (remember, forget, ask_pipeworx), and only the five QuickBooks tools share a qb_ prefix. This creates multiple naming ecosystems with no unified convention.
At 36 tools, this is well above the 25+ threshold for 'too many'. More importantly, the server is named Quickbooks but only 5 tools are accounting-related; the other 31 are unrelated Pipeworx data, prediction-market, memory, and meta tools, making the count both excessive and off-purpose.
For the QuickBooks domain named by the server, the surface is read-only: get customer, get invoice, list accounts, list invoices, and generic query. There are no create, update, delete, payment, bill, deposit, or report operations, which is a significant gap. For the broader Pipeworx data domain it is fairly complete, but that domain is not what the server name promises.