BudgetBakers MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool targets a distinct resource or function: accounts, categories, labels, individual transactions, filtered search, and three separate analytics aggregations. There is no overlap or ambiguity between tools, even among the analytics which are clearly differentiated by output.
Naming Consistency3/5
Four tools follow a clear verb_noun pattern (get_accounts, get_categories, get_labels, get_transaction) and search_transactions also fits. However, the three analytics tools (spending_by_category, cashflow_summary, top_merchants) are noun phrases rather than imperative verbs, mixing conventions. Names remain readable and descriptive, but the inconsistency is noticeable.
Tool Count5/5
Eight tools is well-scoped for a financial data query server. The set covers account discovery, reference data, transaction retrieval/search, and analytics without bloat. Each tool earns its place and the count feels appropriate for the domain.
Completeness4/5
The server provides solid read/analytics coverage: accounts, categories, labels, single transaction, filtered search, and three aggregate views. Minor gaps include lack of a 'list all transactions' endpoint without accountId (search requires it) and no budget/balance history tools, but for a read-centric budget server these are workable limitations.
Average 3.8/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It states the calculation but does not indicate whether the operation is read-only, what constitutes income vs expenses, or the structure of the returned data. Since there is no output schema, this leaves the agent without key 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?
The description is a single, focused sentence that front-loads the core purpose without extraneous detail.
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?
The tool is simple, but without an output schema, the description should clarify the return format. It does not, and it also lacks usage alternatives. However, the core calculation is described adequately for a basic summary 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 input schema documents all three parameters with descriptions, achieving 100% coverage. The description adds no additional parameter semantics, so baseline 3 is appropriate.
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's function with a specific verb ('Calculate') and identifies the three key outputs (income, expenses, net cashflow) and the date-range scope. This distinguishes it from siblings like get_transaction or spending_by_category.
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 guidance is provided on when to use this tool versus alternatives such as spending_by_category or search_transactions. The description implies use for a date range but does not exclude other tools or state prerequisites.
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?
No annotations are provided, so the description carries full burden. It only states the core function without disclosing behavioral details such as aggregation logic, sorting order, or response format. The description adds no context beyond the bare purpose.
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 a single, clear sentence with no redundant words. It immediately states the tool's purpose without extra fluff.
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?
The tool has no output schema and no annotations, yet the description does not describe the return structure or any behavioral specifics. While the schema covers parameters, the agent lacks information about what the response contains, such as merchant names and spending totals. This makes the description insufficient for full contextual understanding.
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?
All four parameters are fully described in the schema (100% coverage), so the description does not need to add parameter semantics. The phrase 'date range' loosely corresponds to dateFrom and dateTo, but no additional meaning is added 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 uses the verb 'find' and specifies the resource 'merchants/payees' with a clear scope 'highest spending in a date range'. This differentiates it from sibling tools like spending_by_category which focuses on categories.
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 usage when a user needs top merchants by spending, but it does not explicitly mention alternatives or exclusion criteria. No comparison with sibling tools is provided, leaving the agent to infer the correct tool 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?
With no annotations, the description carries the transparency burden. It discloses that the tool aggregates (sums) and groups by category, and 'Shows where money goes' adds interpretive context. However, it does not clarify behaviors like inclusion of zero-activity categories, handling of uncategorized transactions, or read-only assurances.
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 short sentences with no filler. It front-loads the core function and keeps the secondary interpretive statement brief, earning a high score for conciseness.
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 no annotations, the description is minimally sufficient but leaves gaps: it does not describe the return shape (e.g., a list of category-total pairs), sorting, or behavior when there is no spending. It covers the core purpose but lacks supporting details.
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 already provides full descriptions for all three required parameters (dateFrom, dateTo, accountId) with 100% coverage. The description adds no additional parameter-level detail beyond the phrase 'for a date range,' so it stays at the baseline.
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 uses a specific verb-resource pair ('aggregate spending by category') and a date-range qualifier, clearly distinguishing it from siblings like top_merchants or search_transactions. It unambiguously explains what the tool does.
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 usage for analyzing spending by category over a given date range, but it does not explicitly mention when to prefer this tool over alternatives like cashflow_summary or top_merchants, and provides no exclusions or alternative suggestions.
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?
No annotations are provided, so the description must fully disclose behavioral traits. It only says 'Search transactions with filters' and mentions the accountId requirement. It does not state that the operation is read-only, describe return types, or mention any side effects. The schema provides some parameter behavior (like date conversion), but the description itself adds little beyond the tool's name.
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 a single, efficient sentence that is front-loaded with the core purpose and the most critical prerequisite. Every word earns its place, and there is no redundancy.
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 tool with 8 parameters but a fully detailed schema, the description plus schema is sufficient. The description covers the key dependency (get_accounts) and the nature of the operation (search with filters). It does not explicitly describe return values, but the tool name and sibling 'get_transaction' make the list-returning behavior inferable. Overall, it is complete enough for an agent to use the tool correctly.
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 input schema has 100% parameter description coverage, with detailed explanations for each parameter (e.g., date formats, client-side search). The description adds no new parameter semantics beyond what the schema already states; the accountId requirement is also already present in the schema. Baseline 3 is appropriate.
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 action ('Search') and resource ('transactions'), with an explicit mention of filters. This distinguishes it from the sibling 'get_transaction', which likely retrieves a single transaction, and positions it as a search/list tool.
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 provides a concrete prerequisite: use get_accounts first to obtain the required accountId. This gives clear usage context, though it does not explicitly discuss when to prefer this tool over siblings like 'spending_by_category' or 'get_transaction'.
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. The verb 'Get' implies a read-only operation, and the mention of income/expense provides some context. However, it does not explicitly state safety, return format, or edge cases, leaving some transparency gaps.
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 concise sentences that front-load the purpose and then provide the use case. No unnecessary words, easily scannable.
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 list tool with one optional parameter, the description is adequate but does not explicitly state the return structure (e.g., array of category objects with ids). Since no output schema exists, the description could be more complete, but the main purpose and usage are clear.
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 describes the single optional 'name' parameter (case-insensitive search) with 100% coverage. The description adds no additional parameter details, so it relies on the schema, which is acceptable but does not go beyond it.
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 action ('Get') and resource ('income/expense categories'), and adds a specific use case (finding categoryId for filtering transactions). It distinguishes itself from sibling tools like get_accounts and get_labels.
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 provides clear guidance on when to use this tool: when you need a categoryId for filtering transactions. It does not explicitly mention alternatives or exclusions, but the intended usage is unambiguous and contextual.
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 full burden. It states the action ('Get user-defined labels/tags') but does not disclose whether it returns all labels when name is omitted, the response format, or other behavioral details. It does hint at the output containing labelId, but this is minimal.
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 a single sentence that conveys purpose and usage without any wasted words. It is front-loaded and appropriately sized.
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 read tool with one optional parameter, the description explains what it does and why to use it. It lacks an explicit return format, but the mention of labelId partially addresses that. With no output schema, a slightly more detailed description could be given, but it is sufficient for basic use.
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 coverage is 100% (the 'name' parameter is described as 'Search labels by name (case-insensitive)'). The tool description adds no further parameter semantics, so the baseline 3 applies.
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?
Description clearly states 'Get user-defined labels/tags' with a specific verb and resource, and adds the purpose of finding labelId for filtering transactions. This distinguishes it from sibling tools like get_categories, which handle a different entity.
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 provides a clear usage context: 'Use to find labelId for filtering transactions.' It implies when to use this tool, but does not explicitly state when not to use or name alternative tools, so it falls short of a 5.
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 burden. It states the tool returns 'full details' without describing what that includes, error behavior, or pagination. For a simple single-ID getter, this is adequate but not rich.
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?
A single, front-loaded sentence with no wasted words. It includes the verb, resource, and essential parameter condition.
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 one-parameter getter with no output schema, the description is sufficiently complete for most usage. It does not describe the return structure but 'full details' provides a reasonable expectation.
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 100% and the only parameter 'id' is documented as 'Transaction ID'. The description adds little beyond restating 'by ID', so baseline 3 is appropriate.
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 uses a specific verb ('Get') with a clear resource ('full details of a single transaction by ID'). It clearly distinguishes this from search_transactions by emphasizing retrieval of a single transaction by unique ID.
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 context is clear: use when you need full details of a single transaction identified by its ID. It does not explicitly state when-not-to-use or name alternatives like search_transactions, but the use case is unambiguous.
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 provided, the description carries the full burden of behavioral disclosure. 'Get all' and 'with balances' clearly indicate the operation is read-only and returns a complete list with balance data. The added note about using accountId for other tools provides useful context. It does not discuss pagination or permissions, but these are not critical for a straightforward 'get' operation.
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, with the primary purpose front-loaded ('Get all financial accounts with balances') followed by a concise usage note. Every word earns its place; there is no fluff or redundancy.
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 read-only list tool with no output schema, the description is complete: it states what is returned (balances), the scope ('all'), and how it fits into the broader workflow (get accountId for other tools). It lacks explicit pagination or error behavior, but these are not essential given the tool's simplicity.
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 input schema describes all three parameters (currency, accountType, includeArchived) with clear descriptions, giving 100% schema coverage. The tool description itself adds no additional parameter detail, so a baseline score of 3 is appropriate—the schema does the heavy lifting.
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 action ('Get all financial accounts') and the resource ('accounts'), with the additional detail 'with balances' specifying what is returned. It also distinguishes itself from sibling tools by positioning this as the entry point to retrieve accountId for other tools.
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 explicitly instructs 'Use this first to get accountId for other tools,' giving clear context for when to call this tool. It does not mention alternatives or exclusions, but since there are no sibling account-specific tools, the guidance is effectively sufficient.
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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