expense-tracker-remote-mcp-server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Each tool targets a distinct operation (add, list, update, delete, summary, budget, trend, search). list_expenses and search_expenses both retrieve expenses, but list uses filters while search uses keyword, and descriptions clarify the difference.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., add_expense, list_expenses, get_summary). This makes the set predictable and easy to navigate.
Tool Count5/5
With 8 tools, the server is well-scoped for expense management. Each tool serves a clear purpose without redundancy or bloat, covering core CRUD plus useful analytics.
Completeness4/5
The surface covers add, list, update, delete, summary, budget check, trend, and search—solid coverage for expense tracking. Minor gaps like a dedicated get-by-ID or budget-setting tool, but these are not critical and can be worked around.
Average 3.2/5 across 8 of 8 tools scored. Lowest: 2.6/5.
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
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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?
No annotations are provided, so the description must carry the full behavioral burden. It only states that a summary is returned grouped by category, but it does not disclose how null category/date parameters behave, whether it aggregates all expenses, or any limitations. The lack of annotation coverage makes this minimal disclosure insufficient.
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 a single, front-loaded sentence with no filler or repetition. It is efficient and easy to parse, though its brevity sacrifices important detail that would improve other dimensions.
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?
With three optional parameters, no annotations, and 0% schema coverage, the description is too sparse. It omits return value details (the output schema exists but the description does not reference it), date filtering behavior, and category null semantics, leaving substantial gaps for a summary tool.
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?
Schema description coverage is 0%, and the description only mentions 'grouped by category,' giving partial meaning to the category parameter. start_date and end_date are completely unexplained, and there is no detail about date filtering, format, or null semantics.
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 uses a specific verb ('Get') and identifies the resource ('spending summary') with a clear grouping dimension ('by category'), which distinguishes it from list-oriented siblings like list_expenses. However, it does not explicitly contrast with get_monthly_trend or get_budget_status, so full sibling differentiation is absent.
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?
There is no guidance on when to use this tool versus alternatives. It does not state that it is for aggregate views as opposed to detailed expense lists, nor does it mention any exclusions, prerequisites, or preferred contexts.
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 disclose behavioral details. It only states that it adds a new expense, without mentioning validation rules, required fields, return behavior, or side effects. This minimal disclosure is insufficient for a mutation operation.
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 a single sentence and is appropriately concise, delivering the core purpose without padding. However, given the lack of detail elsewhere, the brevity is not a strength by itself and could have been expanded with a few more useful phrases.
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 create operation with a rich schema (required fields, defaults) and an output schema, the description is minimally viable but lacks instruction on parameter formats, validation, and usage context. It covers the basic purpose but not enough to guide correct invocation in edge cases.
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 100% undocumented parameters (coverage 0%), and the description provides no parameter semantics. The agent must rely solely on field names and types, which is insufficient for understanding optional fields like 'date' or 'subcategory' and constraints like 'amount' being a number.
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 ('Add') and the resource ('new expense'), which differentiates it from sibling tools like list_expenses, delete_expense, and update_expense. The verb+resource pairing is specific and unambiguous.
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?
There is no guidance on when to use this tool versus alternatives. The description does not mention that this is for creating new records or specify any prerequisites, exclusions, or context, leaving the agent to infer from the tool name and sibling list.
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 provided, the description carries the full burden of behavioral disclosure. It only says 'Update an existing expense's details' without explaining whether it performs a partial update or full replacement, what happens to unspecified fields, or any side effects. This is minimal behavioral information.
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 a single clear sentence with no wasted words, effectively conveying the core purpose. It is front-loaded and concise, though it could arguably include more detail without becoming verbose.
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?
For a mutation tool with 6 parameters, no annotations, and a minimal description, the description is inadequate for disambiguating update semantics (e.g., partial vs. full update). The existing output schema is not referenced, and no context about required ID or return value is given.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, and the description mentions no parameters or their roles. Although parameter names are self-explanatory, the description adds no meaning beyond the raw schema, and the default-null behavior for optional fields is not explained.
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 ('Update') and resource ('existing expense's details'), clearly distinguishing it from siblings like add_expense and delete_expense. It accurately and concisely states 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 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 using add_expense for new expenses or delete_expense for removals. No prerequisites or exclusions are mentioned, leaving the usage context entirely implicit.
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 disclose behavioral traits. It states the core purpose but does not mention the role of the optional 'budget' parameter, whether the operation is read-only (implied by 'check' but not explicitly stated), or any side effects. The lack of detail about parameter behavior and potential default handling leaves significant 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?
The description is a single, concise sentence that communicates the essential purpose without redundancy. It is front-loaded and every word contributes to understanding what the tool does.
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?
For a tool with a single optional parameter and no annotations, the description is too minimal to be complete. It lacks explanation of the 'budget' parameter's behavior and provides no guidance on when to use this tool versus siblings. While the output schema exists, the description’s omission of parameter semantics makes it inadequate for correct invocation.
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 schema has one parameter 'budget' with 0% description coverage, and the description fails to explain its meaning or how it affects the result. The parameter is not mentioned at all, leaving the agent to infer its purpose from the name alone. With no schema descriptions, the description should compensate but does not.
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 'Check' and a clear resource 'budget vs actual spending for current month', which accurately defines what the tool does. It distinguishes itself from sibling tools like get_summary or list_expenses by focusing on budget comparison rather than summary or listing.
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 you want to check budget status for the current month. However, it provides no explicit alternatives or exclusions, such as suggesting get_summary for broader overview or search_expenses for specific transactions. No when-not-to-use guidance is given.
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 provided, the description carries the full burden of behavioral disclosure, but it only says 'Get,' which implies a read operation without explicitly guaranteeing read-only behavior. It does not disclose how trends are aggregated, what time period is covered, or whether any state changes occur.
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, front-loaded sentence with no redundant words. It is appropriately concise for a simple read tool, and every word contributes to the core meaning.
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 the presence of multiple sibling tools and one parameter, the description is too sparse to be complete. It lacks usage guidelines, parameter semantics, and behavioral details, leaving critical decisions to the agent; the output schema does not compensate for these gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not mention the only parameter 'months,' and schema description coverage is 0%. The schema provides just a type and default (6), leaving the agent to guess that 'months' controls the number of months in the trend; the description adds no semantic value.
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' and cleary identifies the resource 'monthly spending trends over time.' This distinguishes it from sibling tools like list_expenses or get_summary, since 'trends over time' signals time-series aggregation.
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 phrase 'trends over time' implies this tool is for time-series analysis rather than listing or summarizing expenses, but no explicit when-to-use or alternative-exclusion guidance is provided. Without references to sibling tools, the agent must infer the appropriate 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 provided, the description must cover behavioral traits. It clearly implies a read-only listing operation, but it does not disclose pagination behavior (despite the limit parameter) or other nuances. The basic behavior is transparent, but additional context is missing.
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, front-loaded sentence with no redundant or filler content. Every word contributes to conveying the tool's basic functionality, making it appropriately concise.
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 core functionality is covered, but the description lacks distinction from the sibling tool 'search_expenses' and fails to mention pagination via the limit parameter. With an output schema present and a simple read tool, the description is minimally adequate but leaves notable gaps in comparative context and parameter 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 description adds meaning to category and date-range parameters by framing them as optional filters, which is helpful given the schema's 0% description coverage. However, it omits the limit parameter entirely and provides no date format details, so the semantics are only partially explained.
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 uses a specific verb 'List' and resource 'expenses', clearly indicating the tool's purpose. It also mentions optional filters, but it does not explicitly distinguish itself from the sibling tool 'search_expenses', so it falls short of a perfect score.
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 like search_expenses. It explains what the tool does but not when to choose it, leaving the agent without decision-relevant context.
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 carry the full burden of behavioral disclosure. It only states the search criterion but does not convey important behavioral traits such as substring vs exact match, case sensitivity, sorting, or pagination behavior. This is a significant transparency gap 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 a single, front-loaded sentence that gets straight to the point. No wasted words or unnecessary details.
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 description is minimal but sufficient for a simple search tool. The presence of an output schema likely documents return values, so that is not a concern. However, the description lacks context on search semantics (e.g., does 'keyword' match exactly or as a substring?), leaving some ambiguity. Given the existence of sibling tools, a bit more context could help disambiguate.
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 description adds meaning to the 'keyword' parameter by clarifying it refers to the description field. However, it says nothing about the 'limit' parameter, and schema description coverage is 0%. Thus, it only partially compensates for the lack of parameter documentation.
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 (expenses), with a specific qualifier ('by description keyword'). This distinguishes it from sibling tools like list_expenses, which presumably lists all expenses without a keyword filter.
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 when to use the tool: when you need to find expenses based on a description keyword. However, it does not explicitly mention alternatives or when not to use it, leaving some ambiguity for an agent deciding between this and list_expenses.
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 disclose behavioral traits. It only states the action, without mentioning permanence, side effects, error handling, or permissions. This is a clear gap for a mutating 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?
A single short sentence that is immediately clear and contains zero filler. Perfectly front-loaded.
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's low complexity, one parameter, and presence of an output schema, the description covers the core action and target. It could mention permanence or error behavior, but these are not critical for a simple delete operation.
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 single required parameter expense_id is given semantic meaning via 'by its ID'. The schema provides type and requiredness, and the description adds the mapping to the resource. Adequate for one simple parameter.
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?
Very specific: verb 'Delete', resource 'expense', and identifier 'by its ID'. Clearly distinguishes from siblings like add_expense, update_expense, and list_expenses.
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?
Usage is implied: to remove an expense, use this tool. But it does not contrast with alternatives (e.g., when to use update_expense instead) or provide exclusions/requirements.
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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