lunchmoney-mcp
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: get-budget-summary targets budget overviews, get-category-spending focuses on category-level data, get-recent-transactions retrieves chronological transaction lists, and search-transactions enables keyword-based queries. There is no overlap in functionality, making tool selection straightforward for an agent.
Naming Consistency5/5All tool names follow a consistent verb-noun pattern with hyphens (e.g., get-budget-summary, search-transactions). The naming is uniform across all four tools, using 'get' for retrieval operations and 'search' for querying, which enhances predictability and readability.
Tool Count4/5With 4 tools, the count is reasonable for a personal finance domain, covering key operations like summaries, category analysis, and transaction retrieval. However, it feels slightly thin as it lacks tools for creating or updating data (e.g., adding transactions or categories), which might be expected in a full-featured finance server.
Completeness3/5The tool set covers read-only operations well, including summaries, category spending, and transaction searches, but there are notable gaps. It lacks CRUD capabilities for transactions, categories, or budgets (e.g., create, update, delete), which limits agents to viewing data without modifying it, potentially causing workflow dead ends.
Average 2.8/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed 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.
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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 provided, the description carries full burden for behavioral disclosure. 'Get recent transactions' implies a read operation but reveals nothing about permissions, rate limits, pagination, error conditions, or what 'recent' means contextually. For a tool with zero annotation coverage, this leaves critical behavioral traits undocumented.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at three words with zero wasted text. It's front-loaded and efficiently communicates the core function without unnecessary elaboration. While under-specified, it earns full marks for brevity and structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is incomplete. It fails to explain what 'recent' means, how results are ordered, what data fields are returned, or how it differs from sibling tools. The agent lacks sufficient context to use this tool effectively without trial and error.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters ('days' and 'limit') well-documented in the schema. The description adds no parameter semantics beyond what the schema already provides. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get recent transactions' is a tautology that essentially restates the tool name without adding meaningful differentiation. It specifies the verb 'Get' and resource 'transactions' but lacks specificity about scope or how it differs from sibling tools like 'search-transactions'. This provides minimal value beyond the name itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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-transactions' or 'get-category-spending'. There's no mention of context, prerequisites, or exclusions. The agent must infer usage from the name alone, which is insufficient for informed tool selection.
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 states the tool retrieves a 'budget summary' but doesn't explain what that summary includes (e.g., categories, totals, trends), whether it's read-only (implied but not explicit), or any limitations like rate limits or authentication needs. This leaves significant gaps for an agent to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the 'budget summary' output contains, how it's structured, or any behavioral traits like error handling. For a tool with two parameters and no structured output documentation, this leaves the agent with insufficient context to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with both parameters ('start_date' and 'end_date') fully documented in the schema. The description adds minimal value by mentioning 'time period,' which aligns with the schema but doesn't provide additional context like format examples or edge cases beyond what's already specified.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('budget summary') with a specific scope ('for a specific time period'), which makes the purpose understandable. However, it doesn't differentiate this tool from its siblings like 'get-category-spending' or 'get-recent-transactions', which likely provide related but different budget/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 Guidelines2/5Does 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. It doesn't mention sibling tools like 'get-category-spending' or 'get-recent-transactions', nor does it specify prerequisites, exclusions, or appropriate contexts for usage beyond the time period requirement.
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 the full burden of behavioral disclosure. 'Get spending' implies a read operation, but it doesn't specify if this requires authentication, has rate limits, returns historical or real-time data, or what format the spending data is in. This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a read operation with two parameters) and the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'spending' entails (e.g., total amount, list of transactions), how results are returned, or any behavioral traits, leaving the agent with insufficient context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description doesn't add any parameter semantics beyond what the schema provides. With 100% schema description coverage, the schema already documents 'category' as 'Category name' and 'days' as 'Number of days to look back' with a default of 30. The baseline score of 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get spending in a category' clearly states the verb 'Get' and resource 'spending in a category', making the purpose understandable. However, it doesn't distinguish this tool from siblings like 'get-budget-summary' or 'get-recent-transactions' which might also involve spending data, 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 Guidelines2/5Does 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. It doesn't mention siblings like 'search-transactions' for broader queries or 'get-budget-summary' for aggregated data, leaving the agent without context for tool selection.
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. While 'search' implies a read operation, the description doesn't address important behavioral aspects like whether this requires authentication, what happens with no results, whether results are paginated, or any rate limits. For a search tool with zero annotation coverage, this leaves significant behavioral questions unanswered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just three words, with zero wasted language. It's front-loaded with the essential information (search transactions) and specifies the mechanism (by keyword) efficiently. Every word serves a clear purpose in this minimal description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with 3 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what constitutes a 'transaction' in this context, what fields are searched, the format of results, or how the search algorithm works. The agent would need to guess about the tool's behavior and output based on minimal information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions searching 'by keyword' which aligns with one of the three parameters. However, with 100% schema description coverage, all parameters are already well-documented in the schema itself. The description adds minimal value beyond what's in the structured schema, meeting the baseline expectation when schema coverage is complete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('search') and resource ('transactions'), and specifies the search mechanism ('by keyword'). However, it doesn't differentiate this tool from its sibling 'get-recent-transactions' which also deals with transactions, leaving some ambiguity about when to use one versus the other.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. It doesn't mention the sibling tools (get-budget-summary, get-category-spending, get-recent-transactions) or explain when keyword searching is preferable to other transaction retrieval methods. The agent receives no contextual usage information.
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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