Kubecost MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no ambiguity. Budget tools (create, delete, get, list, update) are clearly separated from data retrieval tools (get_assets, get_cost_allocation) and the health_check utility. The descriptions reinforce these distinctions, making misselection unlikely.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with snake_case throughout. Budget-related tools use consistent verbs (create, delete, get, list, update) paired with 'budget', while other tools maintain the same naming convention (get_assets, get_cost_allocation, health_check). There are no deviations in style.
Tool Count5/5
With 8 tools, this is well-scoped for a Kubecost server. Each tool earns its place by covering budget management (5 tools), data retrieval (2 tools), and health checking (1 tool). This count is neither too thin nor overwhelming for the domain.
Completeness4/5
The tool set provides complete CRUD coverage for budget rules and includes essential data retrieval and health checks. A minor gap exists in not having tools for other Kubecost features like alerts or recommendations, but core workflows are well-covered and agents can work effectively with what's provided.
Average 2.8/5 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 provided, the description carries the full burden of behavioral disclosure but only states the basic action. It doesn't mention permissions required, whether the operation is idempotent, what happens on failure, or any rate limits. For a mutation tool with 7 required parameters, this leaves significant gaps in understanding how the tool behaves.
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 gets straight to the point with zero wasted words. It's appropriately sized for a basic tool description, though it lacks the detail needed for a complex tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex mutation tool with 7 required parameters, nested objects, no annotations, and no output schema, the description is completely inadequate. It doesn't explain what a 'budget rule' is, what the parameters control, what happens after creation, or any error conditions. The agent would struggle to use this tool correctly.
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?
With 0% schema description coverage and 7 required parameters (including complex nested objects), the description provides no information about what any parameter means or how they should be used. The description doesn't compensate at all for the lack of schema documentation, leaving parameters completely unexplained.
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 action ('Create') and resource ('a new budget rule in Kubecost'), which provides a specific verb+resource combination. However, it doesn't distinguish this tool from its sibling 'update_budget' in terms of when to use one versus the other, which prevents 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 'update_budget' or 'list_budgets'. It lacks any context about prerequisites, timing, or exclusions, leaving the agent to guess based on the tool name alone.
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. It only states the action ('Get asset data') without detailing whether this is a read-only operation, if it requires authentication, what the return format is, or any rate limits. For a tool with 3 parameters and no output schema, this is a significant gap in transparency.
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 extremely concise ('Get asset data from Kubecost'), consisting of a single, front-loaded sentence with no wasted words. It efficiently states the core purpose without unnecessary elaboration, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (3 parameters, nested objects, no output schema) and lack of annotations, the description is incomplete. It doesn't explain what 'asset data' includes, how parameters are used, or what the tool returns. For a data retrieval tool with multiple inputs, more context is needed to guide effective use.
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 description coverage is 0%, meaning parameters are undocumented in the schema. The description adds no information about the parameters (aggregate, filters, window), their meanings, or how they affect the query. With 3 parameters and no output schema, the description fails to compensate for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool's purpose ('Get asset data from Kubecost'), which is clear but vague. It specifies the verb ('Get') and resource ('asset data'), but doesn't distinguish it from potential siblings like 'get_cost_allocation' or explain what 'asset data' entails. The purpose is understandable but lacks specificity about scope or content.
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. With siblings like 'get_cost_allocation' and 'get_budget', it's unclear if this is for financial assets, infrastructure assets, or other types. There's no mention of prerequisites, context, or exclusions, leaving usage ambiguous.
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 full burden for behavioral disclosure. While 'Update' implies a mutation operation, it doesn't describe what happens on success/failure, whether changes are reversible, permission requirements, or rate limits. For a complex update tool with 8 required parameters, this is inadequate.
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 states the core purpose without unnecessary words. It's appropriately sized and front-loaded with the essential information, though it lacks detail.
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 complex mutation tool with 8 required parameters, nested objects, no annotations, and no output schema, the description is severely incomplete. It doesn't explain what the tool returns, error conditions, or provide any parameter guidance. The description fails to compensate for the lack of structured documentation.
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 description coverage is 0%, meaning none of the 8 parameters have descriptions in the schema. The tool description provides absolutely no information about what any parameter means, their formats, or how they interact. This leaves all parameters completely undocumented.
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 action ('Update') and resource ('an existing budget rule in Kubecost'), making the purpose unambiguous. However, it doesn't distinguish this tool from its sibling 'create_budget' beyond the 'existing' qualifier, which is why it doesn't reach the highest 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 'create_budget' or 'delete_budget'. It mentions 'existing budget rule' which implies the budget must already exist, but doesn't specify prerequisites, error conditions, or when other tools might be more appropriate.
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. It states the tool retrieves 'detailed information,' implying a read-only operation, but doesn't specify aspects like authentication requirements, rate limits, error handling, or what 'detailed information' includes (e.g., fields, format). 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.
Conciseness5/5
Is 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.
Completeness2/5
Given 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 1 parameter), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral traits, parameter details, or return values, leaving the agent with insufficient context to use the tool effectively beyond its basic purpose.
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 input schema has 1 parameter with 0% description coverage, and the tool description doesn't add any parameter-specific information. It mentions 'a specific budget rule' but doesn't explain what 'budgetId' represents (e.g., format, source, constraints), leaving the parameter's meaning unclear beyond the schema's basic type.
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 verb ('Get') and resource ('detailed information about a specific budget rule'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_budgets' (which likely returns multiple budgets) or 'get_assets' (which targets different resources), leaving some ambiguity about scope.
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. It doesn't mention prerequisites (e.g., needing a budget ID), exclusions (e.g., not for listing budgets), or comparisons to siblings like 'list_budgets' or 'get_assets', leaving the agent to infer usage from context alone.
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. It only states what the tool does ('Get cost allocation data') without mentioning any behavioral traits such as whether it's read-only, requires authentication, has rate limits, or what the output format might be. This is a significant gap for a tool with parameters and no output schema.
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 directly states the tool's purpose without any unnecessary words. It is appropriately sized and front-loaded, making it easy to parse quickly, though it could benefit from additional context.
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 complexity (4 parameters, no schema descriptions, no output schema, and no annotations), the description is incomplete. It only covers the basic purpose, leaving gaps in usage guidelines, parameter semantics, and behavioral transparency. For a data retrieval tool with multiple parameters, more context is needed to be fully helpful.
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 description coverage is 0%, meaning none of the 4 parameters (accumulate, aggregate, filters, window) are documented in the schema. The description adds no meaning beyond the tool's purpose, failing to explain what these parameters do, their expected values, or how they affect the cost allocation data retrieval. This leaves the parameters largely unexplained.
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 verb 'Get' and the resource 'cost allocation data from Kubecost', making the purpose specific and understandable. However, it doesn't differentiate this tool from sibling tools like 'get_assets' or 'get_budget', which also retrieve data but for different resources, leaving room for improvement in distinguishing its unique scope.
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. There are sibling tools like 'get_assets' and 'get_budget' that might retrieve related data, but the description doesn't mention any context, prerequisites, or exclusions for usage, leaving the agent without clear direction.
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 full burden but only states the action without disclosing behavioral traits. It doesn't mention permissions needed, whether deletion is reversible, side effects, error conditions, or rate limits—critical for a destructive 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 a single, efficient sentence with zero waste—front-loaded and appropriately sized for the tool's scope. Every word earns its place without redundancy.
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 tool's destructive nature, no annotations, 0% schema coverage, and no output schema, the description is incomplete. It fails to address risks, prerequisites, or expected outcomes, making it inadequate for safe agent 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?
Schema description coverage is 0%, and the description adds no meaning beyond the schema. It doesn't explain what budgetId represents, its format, or where to find it (e.g., from list_budgets), leaving the single required parameter undocumented.
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 specific action ('Delete') and target resource ('a budget rule from Kubecost'), distinguishing it from sibling tools like create_budget, update_budget, and list_budgets. It uses precise verb+resource phrasing without tautology.
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 like update_budget or delete operations in other contexts. The description lacks explicit when/when-not instructions or references to sibling tools, leaving usage context implied at best.
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 full burden for behavioral disclosure. It states the tool lists budget rules but doesn't mention whether this requires authentication, how results are returned (e.g., pagination, format), rate limits, or error conditions. This leaves significant gaps in understanding how the tool behaves in practice.
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 directly states the tool's function without unnecessary words. It's front-loaded with the core purpose ('List all budget rules'), making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'budget rules' are in Kubecost context, what format the list returns, or any behavioral aspects like authentication needs. Given the complexity implied by sibling tools (create/update/delete budgets), more context would be helpful.
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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's purpose. This meets the baseline expectation for tools without parameters.
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 action ('List') and resource ('all budget rules in Kubecost'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'get_budget' (which might retrieve a single budget), but the verb 'List all' implies a comprehensive retrieval operation.
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 'get_budget' (for a single budget) or 'get_cost_allocation' (for cost data). It simply states what the tool does without context about appropriate use cases or 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 the full burden of behavioral disclosure. It states the tool checks health and accessibility, implying a read-only, non-destructive operation, but doesn't specify what 'healthy' means (e.g., response codes, latency), whether it requires authentication, or if it has rate limits. For a tool with zero annotation coverage, this leaves key behavioral traits unclear.
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: 'Check if Kubecost API is healthy and accessible.' It's front-loaded with the core purpose, has zero wasted words, and is appropriately sized for a simple tool. Every part of the sentence earns its place by defining the action and target.
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 (0 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral aspects like what constitutes 'healthy' or output format. Without annotations or output schema, more context would be helpful, but the description meets the minimum for a straightforward health check tool.
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 tool has 0 parameters, and schema description coverage is 100%, so there's no need for parameter details in the description. The description appropriately avoids discussing parameters, focusing on the tool's purpose instead. A baseline of 4 is applied since no parameters exist, and the description doesn't add unnecessary information.
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's purpose: 'Check if Kubecost API is healthy and accessible.' It specifies the verb ('Check') and resource ('Kubecost API'), and the health/accessibility focus distinguishes it from sibling tools that manage budgets or retrieve cost data. However, it doesn't explicitly differentiate from potential sibling health-check tools (though none are listed), keeping it from 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. It doesn't mention prerequisites (e.g., before performing operations like create_budget), exclusions (e.g., not for cost queries), or contextual triggers (e.g., after errors). With siblings focused on budget management and cost retrieval, the lack of usage context is a notable gap.
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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