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aws-samples

AWS Cost Explorer MCP Server

Official
by aws-samples
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Quality Checklist

50%
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  • Latest release: v0.1.0

  • Disambiguation3/5

    The tools have some overlap: get_bedrock_daily_usage_stats and get_detailed_breakdown_by_day both provide daily data, with the former being Bedrock-specific and the latter general. This could cause confusion about which tool to use for daily Bedrock costs. The hourly Bedrock tool and EC2 spend tool are distinct.

    Naming Consistency2/5

    Naming is inconsistent: 'get_bedrock_daily_usage_stats' and 'get_bedrock_hourly_usage_stats' follow one pattern, while 'get_detailed_breakdown_by_day' and 'get_ec2_spend_last_day' use different structures (e.g., 'by_day' vs 'last_day', 'usage_stats' vs 'breakdown' vs 'spend').

    Tool Count3/5

    With only 4 tools, the server feels under-scoped for a general 'AWS Cost Explorer' service. It covers only Bedrock and EC2, missing many other services and cost dimensions. However, for a focused subset, 4 tools could be reasonable.

    Completeness2/5

    The tooling covers only Bedrock daily/hourly stats, a generic daily breakdown, and EC2 daily spend. Missing other AWS services, monthly/forecast data, cost anomalies, tag-based queries, and broader exploration features. Significant gaps for a cost explorer tool.

  • Average 3.1/5 across 4 of 4 tools scored.

    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 No Attribution.

  • 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?

    No annotations provided, so description must carry full burden. It only states 'Get' and returns a string, but does not disclose read-only nature, required permissions, rate limits, or any side effects. Insufficient for a data retrieval tool.

    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?

    Description is very brief with structured Args/Returns. Front-loaded with purpose. However, it sacrifices clarity for brevity by omitting important details.

    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?

    No output schema, so description must describe return value – it does as 'formatted string'. But nested parameter object is not explained, and sibling differentiation missing. Incomplete for a parameterized tool with no annotations.

    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?

    Schema coverage is 0% meaning description does not explain parameters. It vaguely mentions 'number of days and region' but omits log_group_name, defaults, and constraints. Schema itself has descriptions, but tool description adds no 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?

    Description clearly states 'Get daily usage statistics with detailed breakdowns', specifying verb and resource. It distinguishes from hourly stats and EC2 spend siblings through 'daily' in name and description.

    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 on when to use this tool versus siblings like get_bedrock_hourly_usage_stats or get_detailed_breakdown_by_day. Agent has no context on selection criteria.

    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 exist, so the description carries full burden. It only states it returns a formatted string, with no mention of side effects, permissions, rate limits, or other behavioral traits. The 'detailed breakdowns' is vague.

    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 with a single sentence plus structured Args/Returns. No redundant information. The format is clear and front-loaded.

    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 tool with one parameter object (three sub-properties) and no output schema, the description provides minimal context. It specifies the return type as a string but not the content format. The 'detailed breakdowns' hint is insufficient for an agent to fully understand the output.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0% for the top-level 'params' property, so description must compensate. It mentions 'number of days to look back and region', which partially maps to the sub-properties, but omits 'log_group_name'. The summary adds some context but incomplete.

    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 it retrieves hourly usage statistics with detailed breakdowns, matching the tool name. It distinguishes from 'get_bedrock_daily_usage_stats' via the 'hourly' qualifier, but does not differentiate from 'get_detailed_breakdown_by_day' or other siblings.

    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 'get_bedrock_daily_usage_stats' or 'get_detailed_breakdown_by_day'. No usage conditions or exclusions are mentioned.

    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?

    Despite no annotations, the description discloses the return structure (nested dict and formatted string) and that it takes a days parameter. It reveals the output format fairly well, though it could mention limitations like max days.

    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 structured with Args and Returns sections. The main purpose is front-loaded. Minor wordiness in Returns could be tightened.

    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?

    There is an internal contradiction: the purpose mentions 'instance type' but Returns only mention 'date, region, and service'. Also, Returns states 'Dict[str, Any]' then says it's a tuple. The description lacks structural details of the nested dictionary. Given no output schema and no annotations, completeness is insufficient.

    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 adds minimal value over the schema: it says 'Parameters specifying the number of days to look back,' but the schema already states that for DaysParam. It does not mention the default of 7, optionality, or constraints. With 0% schema coverage, the description should compensate more.

    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 it retrieves daily spend breakdown by region, service, and instance type. This specific verb and resource differentiate it from sibling tools about bedrock usage and EC2 spend.

    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 on when to use this tool versus siblings. It does not mention prerequisites, alternatives, or context for 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?

    No annotations provided, and description only states it returns raw response or None. Does not disclose read-only nature, potential delays, or error conditions beyond basic None return.

    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?

    Extremely concise, two sentences. Could optionally include usage example or note on API limits, but no excess.

    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 parameterless tool, description covers return value. However, lacking output schema, it could mention typical response structure or error handling.

    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?

    No parameters exist, so baseline is 4. Description does not add parameter info, but none is needed.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    Description clearly states verb 'Retrieve' and resource 'EC2 spend for the last day', distinguishing it from sibling tools focusing on Bedrock usage or daily breakdowns. No ambiguity.

    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 on when to use this tool versus alternatives (e.g., get_detailed_breakdown_by_day). Does not specify prerequisites or context.

    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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