qbo-mcp

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct entity or operation: get tools retrieve single records by ID, search tools list with filters, and chart of accounts is a separate list. No overlap in purpose.
Naming Consistency5/5
All tools follow the consistent pattern `qbo_<verb>_<noun>` where verb is `get_` or `search_`, and nouns are plural for search (customers, vendors, invoices, bills) and singular or collective for get (customer, invoice, vendor, chart_of_accounts).
Tool Count5/5
8 tools cover core QBO entities (accounts, customers, vendors, invoices, bills) without being overwhelming. The count is well-scoped for a focused accounting server.
Completeness2/5
Only read operations are provided (get and search). Missing critical mutation tools (create, update, delete) for any entity, which severely limits the server's utility for typical accounting workflows.
Average 4.1/5 across 8 of 8 tools scored. Lowest: 3.5/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
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  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must bear the full burden. It explains the status filter semantics (open vs paid) and return structure, but it does not disclose side effects, authentication needs, rate limits, or whether the operation is read-only. The description adds marginal behavioral context beyond the parameter list.
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?
The description is concise with clear sections (Args and Returns). Each sentence adds necessary information without redundancy. It efficiently covers parameters and output structure.
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?
Given the tool has 4 parameters and an output schema, the description covers parameter semantics and return envelope. It lacks details on pagination, sorting, or error handling, but the output schema likely fills some gaps. For a search tool, this is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description explains the meaning, format, and defaults for all parameters: ISO dates for date_from/date_to, status optional values, limit cap and default. This adds significant meaning beyond the schema's titles and types.
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?
The description states the tool searches invoices by date range using 'Search invoices created in [date_from, date_to] inclusive.' It clearly identifies the resource (invoices) and action (search). However, it does not explicitly distinguish from sibling tools like qbo_search_bills, so it lacks sibling differentiation.
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 description provides no guidance on when to use this tool versus alternatives such as qbo_get_invoice (single invoice) or qbo_search_bills (bills). There is no 'when-to-use' or 'when-not-to-use' language.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses a read operation returning null on 404, which is helpful. However, it omits any mention of permissions, rate limits, or side effects beyond the basic retrieval behavior.
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?
The description is short but structured with Args and Returns sections, and the main purpose is front-loaded. No extraneous text. It earns a high score for efficiency, though could be slightly more terse.
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?
For a simple single-parameter tool with an output schema (though not shown), the description covers the key behavior: fetching full details, handling 404, and the return envelope. It is complete enough for an agent to understand the tool's basic role.
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 0%, but the description states 'invoice_id: QBO Invoice.Id,' adding meaning that it is the identifier type. This partially compensates for the lack of schema descriptions, but no further details on format or constraints are provided.
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 description clearly states 'Fetch full invoice detail including line items,' which is a specific verb and resource. It distinguishes from sibling tools like qbo_search_invoices (for listing) and qbo_get_customer (for different resource) by targeting a single invoice retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when you have an invoice_id and need full details, but it does not explicitly contrast with search_invoices or provide when-not-to-use scenarios. No explicit guidance on alternatives is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the burden for behavioral disclosure. It mentions 'active only' filtering and the return envelope structure, which adds some value, but lacks details on authentication, rate limits, or pagination behavior.
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?
The description is extremely concise with two short sentences that front-load the purpose and immediately provide useful details about the return format. No extraneous information.
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?
For a simple list retrieval tool with no parameters and an output schema, the description adequately covers purpose and return structure. However, it could mention any potential limits or authentication requirements for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, and schema coverage is 100%. The description does not need to explain parameters, and the baseline for no params is 4, which is appropriate here.
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 description clearly states the verb 'Return' and resource 'full chart of accounts', and specifies that it returns only active accounts, distinguishing it from siblings that focus on individual entities like customers or invoices.
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 description provides no guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusion criteria. The decision must be inferred from tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden and adequately discloses the search behavior: substring, case-insensitive matching on DisplayName. It also specifies the return envelope format. However, it omits potential error conditions or limitations beyond the cap.
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?
The description is extremely concise: a one-sentence purpose followed by structured Args and Returns sections. Every sentence adds value without redundancy, ideal for quick agent parsing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, no nested objects) and the presence of an output schema (with return format described), the description covers the complete input-output contract. It includes the query behavior, parameter defaults, and response structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description fully compensates by explaining each parameter: 'Free-text fragment matched against Vendor.DisplayName' for query and 'Cap on returned vendors (1-1000, default 50)' for limit, adding essential meaning beyond the schema.
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 description explicitly states 'Search vendors by display name (substring, case-insensitive)', providing a specific verb and resource with search criteria. It naturally distinguishes from sibling tools like qbo_get_vendor (single vendor fetch) and qbo_search_customers (different resource).
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 description does not provide guidance on when to use this tool versus alternatives such as qbo_get_vendor, qbo_search_customers, or qbo_search_invoices. It lacks explicit when-to-use or when-not-to-use instructions, leaving the agent to infer from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the return envelope structure and that null is returned on 404, but lacks detail on side effects, auth needs, or rate limits. Adequate but not comprehensive.
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?
The description is concise, with only three lines covering purpose, argument, and return behavior. It is well-structured using Args/Returns labels, and every sentence adds necessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple get-by-ID tool, the description is complete: it specifies the input, the output envelope, and the null case. An output schema exists (as per signals) so detailed return fields are not required in the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds significant value by specifying that customer_id is a 'string-encoded integer per Intuit's API'. This clarifies the expected format beyond the schema's simple type string.
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 description clearly states 'Fetch the full record for a single customer' with a specific verb and resource. It is distinct from sibling tools which target different entities (e.g., invoices, vendors) or search variants, leaving no ambiguity about its purpose.
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 implies usage when the agent needs a complete customer record by ID. While no explicit when-not or alternatives are given, the context is clear and the sibling tools cover other resources, so it adequately guides selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses the return format (JSON envelope with 'data'), specifies null on 404, and implies read-only behavior. This provides sufficient transparency, though could mention idempotency.
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?
The description is two sentences plus structured Args/Returns, front-loading the main purpose. Every sentence adds value with no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description still provides essential details (null on 404) and parameter clarification. It is complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description adds 'QBO Vendor.Id' to clarify the vendor_id parameter. This explains the exact value required, compensating for the lack of schema descriptions.
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 description clearly states 'Fetch the full record for a single vendor', specifying the action, resource, and scope. It distinguishes from sibling QBO tools like qbo_search_vendors by focusing on a single vendor retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when a vendor ID is available, but does not explicitly state when to use this tool versus alternatives like qbo_search_vendors. No when-not or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses return format ('JSON envelope. data.bills'), inclusive date range, optional status filter, and limit cap. This is fairly transparent for a search tool.
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?
The description is well-structured with Args and Returns sections, but a bit verbose (7 lines). It is efficient enough and front-loads key information.
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?
Output schema exists, so description needn't detail return values, but it does mention the envelope. It covers all parameters and their constraints. Missing explicit error handling or pagination, but adequate for a simple search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, so description compensates fully. It explains date_from and date_to as ISO dates with inclusive window, status options (open/paid/null), and limit range (1-2000, default 200), adding significant meaning beyond the schema.
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 description clearly states the tool searches vendor bills with a date range, specifying the resource and action. It distinguishes from siblings like qbo_search_invoices by focusing on bills.
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 explains when to use the tool (search bills by date range) and provides details on the status filter. It lacks explicit when-not-to-use or alternatives, but the context from sibling tools is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the underlying LIKE operator and return envelope. No mention of authentication or rate limits, but these are less critical for a search tool.
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?
The description is concise with two sentences plus structured Args/Returns. It is front-loaded with the purpose and every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description still provides the return structure (JSON envelope) which is helpful. All aspects of the tool are addressed: purpose, parameters, and return format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description adds full context: query is matched via LIKE operator, limit has range 1-1000 and default 50. This adds significant meaning beyond the schema's type declarations.
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 description clearly states 'Search customers by display name (substring, case-insensitive)', specifying the verb, resource, and matching method. This distinguishes it from siblings like qbo_search_bills which search different entities.
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 explains the parameters and their behavior, but does not explicitly state when to use this tool over alternatives. However, sibling tools operate on different entities, so usage context is clear.
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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