qbo-mcp

by ndnfl

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose: batch updates vs single updates, searching vs full fetch vs SQL query, and name resolution. No two tools overlap in functionality.
Naming Consistency4/5
Most tools follow a verb_noun pattern (apply_csv, find_transactions, get_transaction, update_transaction), but 'lookup_ref' uses a verb+noun and 'query' is a single noun, breaking the pattern slightly. Overall consistent snake_case.
Tool Count5/5
6 tools is well-scoped for a QuickBooks Online MCP, covering search, retrieval, updates (single and batch), reference resolution, and raw queries without being excessive.
Completeness2/5
The tool set lacks a create transaction tool, which is a notable gap for typical CRUD operations. While read and update are covered, agents cannot create new transactions, limiting the server's usefulness.
Average 3.5/5 across 6 of 6 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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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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?
With no annotations provided, the description must disclose behaviors. It states 'Fetch the full QBO entity', implying a read-only operation. However, it does not mention side effects, permissions, rate limits, or what 'full entity' entails beyond the hint. Adequate but minimal.
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?
Two concise sentences with no fluff. The first sentence states purpose, the second adds a specific use case. Could be considered slightly under-specified but not wasteful.
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?
Given no output schema and zero parameter documentation, the description is incomplete. It does not explain return format, errors, or the scope of 'full QBO entity'. For a fetch tool, more context (e.g., what the return includes, pagination if any) is expected.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage and the description adds no meaning to parameters 'txn_type' and 'txn_id'. It does not explain valid values, formats, or how to use them. This is a critical gap for parameter usage.
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 clearly states the tool fetches the full QBO entity for a transaction, specifying a distinct resource. Mention of inspecting Line[].Id adds specific use context. However, it does not explicitly differentiate from siblings like find_transactions or query, which could also retrieve transaction data.
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 provides a usage hint ('Use to inspect Line[].Id and current values') but lacks explicit guidance on when to use this tool versus alternative siblings. No exclusions or prerequisites are mentioned, leaving the agent to infer 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?
With no annotations, the description covers the key behavioral modes (dry_run vs commit) and mentions return format (per-transaction results plus tally). However, it does not disclose potential destructive actions from commiting, error handling, or prerequisites.
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 concise at four sentences, front-loaded with the main action, and every sentence adds necessary information about columns, behavior, and output. Could be slightly more structured but efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and low schema coverage, the description explains the tool's core functionality and return format adequately. However, it lacks details on error handling, CSV validation, or impact on existing data, which would be helpful for a batch update tool.
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?
The schema has 0% description coverage, so the description must add meaning. It explains the dry_run parameter's default and effect (resolves refs/plans vs commits), but does not describe the csv_path parameter format or constraints beyond listing column names. Partial value added.
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 clearly states the tool applies a CSV of changes in batch, specifying the column structure. It references 'qbo-apply' which helps contextualize, though it's not a direct sibling. The verb 'Apply' and resource 'CSV of changes' is specific.
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 mentions 'Mirrors qbo-apply' but does not explain when to use this tool versus the listed siblings like update_transaction or query. No explicit when-to-use or when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the function. Does not disclose read-only nature, authentication requirements, or error behavior. Minimal behavioral context.
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?
Extremely concise: one sentence plus a list of entity types. No unnecessary words or structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple lookup with 2 params and no output schema, the description is adequate but leaves gaps: return format, uniqueness, error handling not mentioned. Could benefit from specifying output structure.
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%. The description adds value by listing valid entity_type values (Account, Class, Department, Customer, Vendor). However, no constraints or details for the 'name' parameter are given.
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 resolves a list-entity name to its QBO Id, specifies the entity types (Account, Class, Department, Customer, Vendor), and is distinct from sibling tools which involve CSV import, transaction queries/updates.
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?
No explicit guidance on when to use this tool versus siblings like 'query' or 'find_transactions'. Lacks prerequisites, alternatives, or when-not-to-use instructions.
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 provided, so description bears full burden. States 'read-only' and 'returns raw entity rows,' but omits details like error handling, rate limits, or SQL constraints beyond the example.
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?
Two sentences, front-loaded with action, example, and return type. No redundant 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 return values need not be described. Simple tool with one param; description covers purpose, example, and nature. Minor gaps in error handling or security.
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?
Single 'sql' parameter with 0% schema coverage. Description adds value with QuickBooks context and an example query format, though could explicitly restrict to SELECT statements.
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?
Clearly states the tool runs a read-only QBO SQL query with an example (SELECT * FROM Class) and mentions returns raw entity rows. Distinguishes from sibling tools by emphasizing read-only nature.
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?
No explicit guidance on when to use this tool versus siblings like find_transactions or lookup_ref. The read-only hint is implicit but lacks context for selection.
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 mentions returning Id and key fields, but does not disclose pagination behavior, rate limits, or whether the operation is read-only (though implied). The limit parameter is not explained in the description.
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 three sentences with no redundancy. It starts with the core purpose, then lists txn_type values, and finally explains date range and entity filters. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 9 parameters, no output schema, and no annotations, the description is somewhat incomplete. It does not explain the output structure beyond 'Id + key fields', nor does it clarify the behavior of the limit parameter or single date parameter. The description is adequate but not fully comprehensive for a parameter-rich search tool.
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%, so the description must explain parameters. It covers txn_type, date_start/date_end, customer, and vendor, but not doc_number, date, amount, or limit. The description adds some meaning beyond the schema (e.g., txn_type list, customer/vendor mapping), but incomplete parameter documentation reduces effectiveness.
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 it searches QBO transactions by metadata and returns Id plus key fields. This differentiates from siblings like get_transaction (single transaction retrieval) and update_transaction (modification). The verb 'Search' and resource 'transactions' are specific.
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 specifies that txn_type must be one of the listed types, and provides guidance on using customer vs vendor filters. It states 'provide at least one filter', implying when to use additional parameters. However, it does not explicitly mention when not to use this tool compared to alternatives like get_transaction or query.
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. It discloses that dry_run defaults to True, resolving references and reporting a plan without writing, and that passing dry_run=False commits the update. This is a key behavioral trait. It does not mention side effects or error handling, but covers the essential operational 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 concise: three sentences that front-load the purpose, then detail the change format and dry_run flag. Every sentence adds necessary information with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should clarify what the tool returns (plan on dry_run, confirmation or error on commit). It mentions 'reports the plan' but does not specify the response format. Also, it lacks context on permissions or error scenarios. While core usage is covered, completeness is slightly lacking.
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%, so the description must compensate. It adds detailed meaning for the 'changes' parameter (structure and fields) and 'dry_run' behavior. The 'txn_type' and 'txn_id' are not elaborated, but their purpose is clear from context. Overall, it adds significant value 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 it applies one or more field changes to a single transaction. The verb 'Apply' and resource 'transaction' are specific. It distinguishes from siblings like get_transaction (read) and find_transactions (search).
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 explains how to use the tool (change format, dry_run flag) but does not provide context on when to choose this tool over siblings. No explicit when/when-not or alternatives are mentioned, though the dry_run feature is well-explained for safe usage.
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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