Wallet BudgetBakers MCP

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct resource (accounts, records, categories, budgets, goals, labels, standing orders, rules, API usage). The only potential overlap is get_records vs get_records_by_id, but the latter explicitly retrieves by IDs, making the distinction clear.
Naming Consistency5/5
All tools follow the get_<resource> pattern with consistent snake_case. The sole variation, get_records_by_id, still adheres to the overall convention and is predictable.
Tool Count5/5
10 tools is well-scoped for a read-only financial data API, covering all major entities without unnecessary bloat or missing core resources.
Completeness5/5
The tool set provides comprehensive read-only coverage of the budgeting domain: accounts, transactions, categories, budgets, goals, labels, standing orders, rules, and API usage. No obvious gaps exist for querying financial data, and filters allow for detailed retrieval.
Average 4.1/5 across 10 of 10 tools scored. Lowest: 3.4/5.
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 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.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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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 carries the full burden. It does not disclose side effects, authentication requirements, rate limits, or what specific statistics are returned. The verb 'Get' implies read-only, but this is not explicitly stated, and no other behavioral context is given.
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 and front-loaded with the core purpose. The Arg section is compact, but the inclusion of 'ctx' (not in schema) adds minor noise. Overall, it is efficient and earns its place without 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 the tool's simplicity (one optional parameter, output schema exists), the description is minimally adequate. It covers the period format, but lacks usage guidance and behavioral transparency. The output schema likely explains return values, so that is not a gap. Still, the absence of when-to-use context leaves the description incomplete for a fully informed agent.
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 valuable context by specifying the period format (Xdays, Xweeks, Xmonths) with examples. This goes beyond the schema's basic string type and default value, helping the agent construct valid inputs. However, it also mentions 'ctx' which is not in the schema, slightly muddying the parameter list.
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 'Get API usage statistics' with a specific verb and resource. It is distinct from sibling tools like get_accounts, get_records, etc., which focus on other data domains.
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. There are no exclusions, prerequisites, or alternative tool suggestions. The description simply states what the tool does without contextual usage direction.
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 pagination parameters (limit/offset) and filter syntax, which is useful. However, it doesn't mention sorting, combination rules, or other operational behaviors beyond basic parameter ranges.
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 front-loaded with a clear purpose, followed by a structured Args list where every line adds value. It's a bit lengthy but not wasteful; no unnecessary filler.
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 6-parameter read-only list tool, the description covers parameter semantics, pagination, and filtering well. The output schema exists to describe return shape, so not explaining it is fine. Minor gaps like sorting or filter combination rules exist, but overall it's sufficient for an agent to select and invoke this 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?
The input schema has zero descriptions, but the tool description compensates fully. It explains limit range/default, offset semantics, rule_id exact matching, name filter prefixes (eq., contains., contains-i.), and date filter formats with examples—significantly more than the schema provides.
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 'gets auto-categorization rules for records' and explains what those rules do. This is a specific verb+resource pairing, though it doesn't explicitly distinguish itself from sibling tools like get_categories or 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used when retrieving auto-categorization rules, but gives no explicit guidance about when to use it versus alternatives, nor any when-not examples. The context is implied rather than spelled out.
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 bears the full burden of behavioral disclosure. It implies a read-only operation ('Get all') and describes available filters, but it does not explicitly state that no data is modified, mention authentication limits, or describe pagination edge cases. The detail about 'current/target amounts and deadlines' adds some context beyond the tool name.
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: a single front-loaded sentence followed by a structured Args list. The list is easy to scan and adds necessary detail. The inclusion of 'ctx' as a parameter (not present in the schema) and the slightly cryptic note example are minor inefficiencies, but overall the description earns its place.
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?
The tool has an output schema, so return values are covered elsewhere. The description explains the resource, key fields, pagination, and filtering options. It does not mention any side effects or authorization requirements, but for a read/filter tool with no annotations, this is reasonably complete. Minor gaps include not addressing edge cases like empty results or combined filters.
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 schema description coverage is 0%, so the description must compensate. It does so well by explaining each parameter's purpose, including filter syntax examples like 'gte.2025-01-01' and prefix modifiers (eq., contains., contains-i.). However, it lists 'ctx' which is not in the schema, and the note example 'contains-i.vacation' is somewhat unclear, preventing a perfect score.
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 'Get all savings goals with current/target amounts and deadlines', which specifies the verb (get), resource (savings goals), and the key data fields. This distinguishes it from sibling tools like get_budgets or get_categories, which target different financial entities.
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 retrieving savings goals and explains pagination and filter options, but it does not explicitly contrast with sibling tools or state when not to use this tool. Its context is clear but lacks exclusionary guidance, so it sits at a mid-level score.
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 carries the full burden of behavioral disclosure. It mentions the data returned (limits, spent amounts, periods) and explains pagination via 'limit' and 'offset' parameters. However, it does not explicitly state that the operation is read-only, nor does it describe default sorting, authentication requirements, or any side effects. The 'Get' verb implies safety, but the description lacks depth beyond that.
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 efficiently structured: a one-line summary followed by a compact parameter list. Every line provides necessary information without redundancy. The 'Args:' block is clearly organized and scannable, making it easy for an agent to parse.
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 list tool with an output schema and optional filters, the description is nearly complete. It explains the tool's purpose, return content, and all filter parameters. Minor gaps include lack of default sorting order and mention of how filters combine, but the presence of an output schema reduces the need to describe return values. Overall, it provides enough context for correct invocation.
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 schema has 0% coverage, so the description must compensate. It does so effectively by explaining each of the 7 parameters with filter semantics, including prefix operators for 'name' (eq., contains., contains-i.) and date filtering examples for 'created_at' and 'updated_at'. This adds significant meaning beyond the schema's type/default information. It would be a 5 if it covered all possible filter operators, but it gives enough examples to be highly useful.
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 'Get all budgets with their limits, spent amounts, and periods.' This is a specific verb + resource combination that unambiguously identifies the tool's function and distinguishes it from sibling tools like get_accounts or get_categories. The added detail about what data is returned solidifies the purpose.
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 through the phrase 'Get all budgets' and the filter parameters, but it does not explicitly state when to use this tool versus alternatives or provide any exclusions. For example, there is no guidance on when to use get_budgets instead of other listing tools. This makes the usage context implied rather than explicit.
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 carries the full burden of behavioral disclosure. It explains pagination parameters and filter semantics (e.g., prefix matching, date operators) and mentions the hierarchical structure, but it does not explicitly state that it is a read-only operation or describe what happens on empty results. 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?
The description is well-structured: a one-line purpose, a brief note on hierarchy, usage context, and a concise Args block. Every sentence adds necessary information, and the format is easy to scan.
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 existence of an output schema, the description need not detail return values. It covers filtering, pagination, and hierarchical relationships, which is sufficient for a list/filter tool. It could mention sorting or error behavior, but overall it is quite complete.
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%, so the description must compensate. It does so thoroughly: each parameter gets a meaningful explanation beyond the raw schema, including ranges (limit 1-100), defaults, filter semantics, and examples for date filters. This adds substantial value.
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 'Get spending/income categories' with a specific verb and resource, clearly distinguishing it from sibling tools that handle accounts, records, budgets, etc. However, it does not explicitly contrast with alternatives, so it stops 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description notes that categories are hierarchical and advises using category IDs to filter records by category, which gives practical context for when to use this tool. It does not explicitly mention when not to use it or name alternative tools, but the guidance is clear enough for typical usage.
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 burden of disclosing behavior. It does explain filtering operators (e.g., 'prefix: eq., contains., contains-i.') and provides date examples, which adds useful behavioral detail. However, it does not explicitly state read-only status, pagination caveats, or any side effects, leaving some ambiguity for an agent relying solely on this 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 compact and well-structured: a one-sentence purpose followed by a bullet-style Args list. Every line adds value, and the param details are immediately scannable. No fluff or repetition of schema defaults.
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 that an output schema is present, the description need not explain return values. It covers filtering, pagination, and parameter semantics thoroughly. However, it omits any mention of default sort order or how results are ordered, which would be useful for a list endpoint. Overall, it is complete enough for effective invocation.
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 documenting every parameter with meaning and examples. It explains the filter syntax for 'name', the date format for 'created_at'/'updated_at', and pagination semantics for 'limit'/'offset'. This is far more helpful than the bare schema properties.
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 opens with 'Get custom labels (tags) used to organize records,' which is a specific verb+resource pair that clearly differentiates this tool from sibling tools like get_records or get_categories. The term 'custom labels' is unambiguous and immediately conveys the tool's scope.
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 clearly implies when to use the tool (when you need to fetch labels/tags) but does not provide explicit when-not-to-use guidance or mention alternative tools. Since all sibling tools are list/retrieval operations, the unique focus on labels provides implicit context, but exclusions are absent.
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 full burden. It discloses input format and the 30-ID limit, but does not specify behavior when some IDs are invalid (e.g., error vs. partial results). For a simple read tool, this is a noticeable gap, though the core behavior is clear.
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 brief and front-loaded with the main purpose in the first sentence. The 'Args' section is slightly redundant but adds clarity; no wasted words overall.
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 one parameter and an output schema, the description covers the essentials: purpose, parameter format, and limit. It lacks error-handling details, but that is a minor gap for such a simple tool. The output schema handles return value documentation.
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%, so the description must compensate. It fully explains the record_ids parameter with format and example ('Comma-separated record IDs (e.g. "id1,id2,id3")') and adds the max 30 constraint, going well 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 'Get specific records by their IDs', which is a specific verb+resource that distinguishes it from siblings like get_records. It also adds detail about comma-separated IDs and a max of 30, making the purpose unambiguous.
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 you have specific record IDs, contrasting with get_records which likely retrieves all records. It provides clear context but does not explicitly name alternatives or state when-not-to-use, so a slight deduction.
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 implies a read-only operation via 'Get' and 'Shows', and gives insight into the return type (planned future transactions). However, it does not explicitly state that it is non-destructive, nor does it disclose error handling, permissions, or other side effects.
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 appropriately sized, starting with a clear one-sentence purpose, then a brief example of what it returns, and a structured Args list. Every sentence earns its place, and the parameter documentation is concise and 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?
The description covers the tool's purpose and all parameters effectively. With an output schema present, return values need no explanation. However, it lacks some details like how filters combine, default ordering, or timezone handling, leaving minor gaps for a 7-parameter 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?
The schema has 0% description coverage, but the description fully compensates by documenting all 7 parameters in the Args section. It provides types, defaults, and concrete examples (e.g., 'name: use prefix: eq., contains., contains-i.', 'created_at: gte.2025-01-01'), adding significant meaning beyond the raw 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 'Get recurring/scheduled payments (standing orders)', giving a specific verb and resource. It distinguishes itself from sibling tools by focusing on standing orders, and further clarifies with examples like 'bills, subscriptions, salary'.
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 clearly indicates when to use this tool by explaining it shows planned future transactions (bills, subscriptions, salary). It does not explicitly mention alternatives or when not to use, but the context is clear enough for an agent to decide.
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 pagination behavior (limit/offset), filter semantics with prefix syntax (eq., contains., contains-i., gte.), and the discovery workflow. It does not explicitly state read-only/auth requirements, but 'Get' strongly implies a safe read operation, and the detailed parameter behavior adds useful 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 front-loaded with the purpose, followed by a one-line usage note, then a clean bulleted parameter list. Every line adds value, and the length is appropriate for the number of parameters.
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?
Despite having an output schema that covers return values, the description still explains the relationship to get_records, pagination, filtering, and all parameter semantics. It is complete for a list/discovery tool with this complexity.
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?
The input schema has zero descriptions, yet the tool description documents all 9 parameters with types, defaults, examples, and filter syntax. This fully compensates for the schema's lack of coverage and goes well beyond 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 opens with a specific verb and resource: 'Get all financial accounts (bank accounts, cash, cards, etc.)'. It also differentiates itself from siblings by noting it should be used first to discover account IDs, clearly positioning it as the account-discovery 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?
It explicitly instructs 'Use this first to discover account IDs — you'll need them for get_records()', which provides a clear use case and relationship to an alternative tool. It does not list when-not-to-use scenarios, but the guidance is strong enough for an agent to select it appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses critical behaviors: max date range 370 days, default 3 months if no date filter, transfer records identified by transferId/transferAccountId, and detailed filter syntax. This goes far beyond a basic description.
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 and front-loaded with the most critical info (required account_id, date limits), but it has some redundancy: filter examples are given in a dedicated section and then repeated in the args list. While this improves self-containedness, it slightly hurts conciseness.
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 complexity (14 params, no annotations, output schema present), the description provides comprehensive context: required parameters, default pagination, filter formats, and transfer behavior. It is sufficient for an agent to select and invoke correctly.
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%, so the description fully compensates. Every parameter (14 total) is listed with examples and explanations (e.g., 'note: Filter by note text (use prefix: contains-i.grocery)' and 'amount: Filter by amount (use prefix: gte.100,lte.500)'). This adds substantial meaning beyond the raw 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 'Get financial records (transactions) for a specific account.' This is a specific verb+resource with scope, and it distinguishes from siblings like get_records_by_id (single record) and get_accounts (accounts).
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?
It explicitly says 'account_id is required. Use get_accounts() first to find it,' providing a prerequisite and directing to a sibling tool. It also clarifies default behavior (last 3 months) and max date range. However, it does not explicitly contrast with alternatives like get_records_by_id for single-record retrieval.
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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curl -X GET 'https://glama.ai/api/mcp/v1/servers/lapin7771n/wallet-budgetbakers-mcp'

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