qb_list_invoicesGet recent invoices with number, customer, amount, due date, and payment status. Use qb_get_invoice for full line-item details.
| Name | Required | Description | Default |
|---|---|---|---|
| max_results | No | Maximum number of invoices to return (default 25, max 1000) | |
| start_position | No | Starting position for pagination (default 1) |
| 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": {
+ "QueryResponse": {
+ "description": "Array of invoices with number, customer, amount, due date, and status",
+ "items": {
+ "properties": {
+ "CustomerRef": {
+ "description": "Reference to customer",
+ "type": "object"
+ },
+ "DocNumber": {
+ "description": "Invoice number",
+ "type": "string"
+ },
+ "DueDate": {
+ "description": "Due date",
+ "type": "string"
+ },
+ "Id": {
+ "description": "Invoice ID",
+ "type": "string"
+ },
+ "TotalAmt": {
+ "description": "Total invoice amount",
+ "type": "number"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "type": "object"
+ }
+ ],
+ "type": "object"
+}Input schema / examplesAdded value: +[
+ {
+ "max_results": 25
+ },
+ {
+ "max_results": 50,
+ "start_position": 26
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint. Description adds value by specifying returned fields and pagination parameters, consistent with 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?
Two sentences, no wasted words. First sentence states purpose and output, second provides alternative. 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?
Description covers purpose, output fields, and sibling alternative. Schema covers parameters and pagination. Near complete for a simple list 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?
Schema coverage is 100% with clear parameter descriptions. Description does not add new parameter context but is sufficient. Baseline 3 is appropriate.
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?
Description clearly states verb 'Get', resource 'invoices', and lists specific fields returned (number, customer, amount, due date, payment status). It also distinguishes from sibling qb_get_invoice for full details.
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?
Explicitly recommends qb_get_invoice for full line-item details, guiding selection between related tools. Does not explicitly state when not to use, but context is clear.
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.