AmexAnalysis-MCP

by ogprotege

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v2.0.0
Disambiguation5/5
Each tool targets a distinct analytical aspect: overall spending, subscriptions, specific vendors, anomalies, category breakdown, and export. No meaningful overlap exists between them.
Naming Consistency4/5
Five of six tools follow a clear verb_noun convention (analyze_*, find_*, export_*). The outlier, spending_by_category, uses a noun phrase but is still readable and not jarringly inconsistent.
Tool Count5/5
Six tools is a well-scoped count for a specialized spending-analysis server. Each tool covers a distinct need without redundancy or bloat.
Completeness4/5
The surface covers the core analysis lifecycle: overall analysis, drill-downs (vendor, category), anomaly detection, and export. Minor gaps like time-period comparison or raw transaction listing could be added, but the current set supports typical workflows.
Average 3/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 6 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing side effects. It only says 'export,' which implies file creation, but does not mention overwrite behavior, return values, or whether it uses existing analysis results or reads fresh data.
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 one concise sentence with no redundant words. While it is brief, the structure is efficient and easy to scan.
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 absence of an output schema and only a one-line description, the tool leaves many questions unanswered about the export process, file formats, and its relationship to sibling tools. It is not complete enough for an agent to understand the full pipeline.
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 100%, with all three parameters (csvPath, format, outputPath) having descriptions in the schema. The description adds no additional parameter-level meaning, so the baseline score of 3 is appropriate.
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 uses a clear verb 'export' with a resource 'comprehensive spending analysis,' which is distinct from the sibling analysis tools. However, 'comprehensive' is vague and does not specify what the analysis entails or what the output contains, leaving room for 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 is provided on when to use this tool relative to alternatives, prerequisites, or whether it should follow another analysis tool. Sibling tools such as analyze_amex_spending or find_subscriptions suggest a workflow, but the description does not connect to it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey whether the tool performs reads, writes, or other side effects. 'Get detailed analysis' implies a read operation but does not explicitly state what happens, what data is accessed, or what the output contains. This leaves significant behavioral ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no fluff, front-loading the action. It is appropriately sized for a simple tool, though it lacks detail that would be useful in the sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotation support, the description does not explain what 'detailed analysis' returns or what constitutes a successful invocation. The agent cannot infer what to expect from the tool's response, making it incomplete for a tool without an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters with clear descriptions for csvPath and vendorName. The tool description adds no additional parameter information, so it meets the baseline but does not exceed it.
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 analyzes a specific vendor, using the verb 'get' and resource 'specific vendor'. However, it does not distinguish from sibling tools like analyze_amex_spending or spending_by_category, so it misses the top 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?
No guidance is provided for when to use this tool versus alternatives. There is no mention of exclusions or context that would help the agent select it over siblings like find_subscriptions or find_anomalies.
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, the description must communicate behavioral traits, but it only states the tool's purpose. It does not disclose what the tool returns, whether it is read-only, how severity thresholds affect output, or any side effects, offering minimal 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 a single, front-loaded sentence with no unnecessary words. It states the core function efficiently and meets the conciseness standard.
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?
The tool has no output schema and no annotations, so the description should explain what the agent can expect from the tool. It only gives a high-level goal with no mention of output format, severity behavior, or practical usage context, making it incomplete for an anomaly-detection tool.
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 100% with clear descriptions for both csvPath and severityThreshold. The tool description adds no parameter-level detail beyond the schema, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Find') with a distinct resource ('spending anomalies and potential fraud'), which clearly separates it from siblings like find_subscriptions and analyze_amex_spending. However, 'potential fraud' is broad and not further qualified, so it stops short of a fully precise purpose statement.
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 about when to use this tool versus alternatives. The sibling tools imply different purposes, but the description does not state conditions, prerequisites, or exclusions, leaving the agent to infer usage from the 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 must convey behavioral traits. It only says 'Analyze spending broken down by category' without explaining what the output looks like, how categories are determined, whether any data is written or exported, or any other side effects. This leaves significant ambiguity for the agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no waste. It front-loads the core action and scope. While extremely terse, it does earn its place by stating the primary purpose, though it could benefit from a bit more detail without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool takes a single parameter and has no output schema, but with no annotations, the description must carry more weight. It fails to disclose the return format, aggregation details, or how this tool differs from closely related siblings. The context is insufficient for an agent to reliably invoke the tool and interpret the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides a description for csvPath ('Path to Amex CSV file'), and schema coverage is 100%. The description adds no extra parameter semantics beyond what the schema defines. Thus, the baseline of 3 applies.
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 'Analyze spending broken down by category' clearly identifies the verb (analyze), resource (spending), and the specific scope (broken down by category). This distinguishes it from sibling tools like 'analyze_vendor' (vendor breakdown) and 'find_anomalies' (anomaly detection). Though 'analyze' is generic, the category breakdown adds specificity.
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 it should be used when a category-level breakdown of spending is needed, but it does not explicitly state when to use it versus alternatives like 'analyze_amex_spending' or 'analyze_vendor'. There is no mention of when not to use it or which sibling tools are preferred for different scenarios.
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, the description carries full responsibility for behavioral disclosure. It states that the tool analyzes spending from a CSV, but does not mention whether it writes output files, overwrites existing files, returns data in-memory, or has any side effects. The optional outputPath parameter hints at file output, but the description fails to clarify behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that front-loads the tool's purpose. It contains no redundant information or fluff, making it appropriately concise and easy 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?
Given the tool's relative simplicity (one required parameter, two optional, no nested objects) and the well-documented schema, the description is adequate. However, the absence of an output schema means it could add more detail about what the analysis result looks like or how the output is delivered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides complete descriptions for all three parameters, including the enum for outputFormat and its default value. The description adds no additional parameter-level meaning beyond restating the overall purpose, so it does not exceed what the schema already conveys.
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 analyzes Amex credit card spending from a CSV file, identifying the specific resource (Amex spending), action (analyze), and input source (CSV). It does not explicitly distinguish itself from sibling tools like spending_by_category or analyze_vendor, but the 'Amex CSV' qualifier provides some differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 does not mention alternatives such as spending_by_category, find_anomalies, or analyze_vendor, nor does it give any exclusions or prerequisites. Usage context is only implied by the tool's name and description.
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 present, so the description carries the full burden. It implies a read-only search but gives no details on what constitutes a subscription, how matches are determined, or what the output contains. The word 'find' suggests no side effects, but that is not explicit.
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?
One sentence with no filler; it is concise and front-loaded. The brevity is appropriate given the simple structure, though it contributes to the transparency gap.
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 one-parameter tool, the description covers the core action, but it does not explain the return format or edge cases, nor how subscriptions are defined. Given no output schema and no annotations, the description leaves some ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully documents csvPath with 'Path to Amex CSV file', and the description adds no extra meaning about parameter constraints or behavior. With 100% schema coverage, the baseline of 3 is appropriate.
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 tool finds subscriptions within Amex transactions, using a specific verb and resource. The noun 'subscriptions' distinguishes it from sibling tools like find_anomalies or spending_by_category.
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 siblings like find_anomalies or analyze_amex_spending, nor any exclusions or prerequisites. The context is implied solely by the tool name.
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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