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popechia

ABANCA MCP Server

by popechia
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Server Quality Checklist

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  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one retrieves a list of bank accounts with balances, while the other retrieves transactions for a specific account. There is no overlap or ambiguity in their functions, making it easy for an agent to select the correct tool based on the need.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern with 'get_' prefix, using snake_case throughout. The naming is predictable and readable, with no deviations or mixed conventions, ensuring clarity and ease of use.

    Tool Count2/5

    With only two tools, the server feels under-scoped for a banking domain that typically involves operations like creating accounts, updating details, or initiating transfers. This limited set may hinder agents from performing comprehensive banking tasks, indicating a mismatch with the apparent scope.

    Completeness2/5

    The tool surface is severely incomplete for a banking server, covering only retrieval of accounts and transactions. Missing are essential CRUD operations such as creating or updating accounts, initiating transfers, or managing payments, which are critical for typical banking workflows and will likely cause agent failures.

  • Average 3.1/5 across 2 of 2 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 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?

    No annotations provided, so description carries full burden. It discloses only the basic read operation ('Retrieves') but omits critical financial API behaviors: pagination limits, rate limiting, data freshness/real-time vs cached status, authentication requirements, or error handling for invalid IBANs.

    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?

    Single 9-word sentence is efficient and front-loaded (verb first). No redundancy or fluff. However, for a financial data tool handling sensitive transaction history, this brevity may be excessive minimalism that sacrifices necessary behavioral context.

    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?

    With 100% schema coverage and only 2 simple parameters (one optional), the description is minimally adequate for invocation. However, lacking output schema and annotations, and given this retrieves financial transaction data, the description is incomplete regarding data volume, format expectations, and result set boundaries.

    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 coverage is 100% with both 'iban' and 'days_ago' fully documented in the schema. The description mentions IBAN generically but does not add param-specific semantics, syntax guidance, or usage notes beyond what the schema already provides. Baseline 3 appropriate for high schema coverage.

    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 specific verb 'Retrieves' and resource 'transactions' with scope 'for a specific bank account IBAN'. However, it does not explicitly distinguish from sibling tool 'get_bank_accounts' (which likely lists accounts vs. this retrieving transaction history for a specific account).

    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 provided on when to use this tool versus alternatives, nor prerequisites (e.g., suggesting users may need 'get_bank_accounts' first to obtain valid IBANs). The description is purely functional with no contextual usage hints.

    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 disclosure. It provides minimal behavioral context by mentioning 'balances' (indicating account-level financial data is returned), but lacks details on pagination, authentication requirements, rate limits, or the complete structure of the returned 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 single-sentence description is efficient at 9 words, front-loaded with the action ('Retrieves'), and contains no extraneous text. However, similar to the calibration example, it doesn't quite achieve a 5 as it could slightly improve by noting the unfiltered nature of the retrieval given the empty parameter schema.

    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 zero parameters and no output schema, the description provides the minimum viable context by identifying the resource type and key returned attribute (balances). However, given the lack of structured output schema, it should ideally describe the return format (e.g., list of objects with account IDs and balances) to be considered complete.

    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?

    Per the rubric, 0 parameters equals a baseline score of 4. The description appropriately does not attempt to invent parameter semantics, though it could have noted 'accepts no filters' or 'retrieves all accessible accounts' to clarify the empty schema behavior.

    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 ('Retrieves') and resource ('bank accounts'), and mentions 'balances' which distinguishes it from the sibling tool 'get_account_transactions' (accounts vs. transactions). However, it does not explicitly reference the sibling relationship or when to choose one over the other, which prevents a 5.

    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 states what the tool does but provides no guidance on when to use it versus alternatives, prerequisites (e.g., authentication), or exclusion criteria. The distinction from 'get_account_transactions' must be inferred from the resource names rather than explicit guidance.

    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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