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OjasKord

Data Compliance Classifier MCP

by OjasKord
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JavaScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.32

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: validate_data_safety performs full AI classification, get_safety_report provides detailed compliance reports for flagged payloads, and validate_data_safety_lite offers fast pattern-only pre-screening. There is no overlap or ambiguity.

    Naming Consistency5/5

    All tool names use a consistent verb_noun pattern in snake_case (validate_data_safety, get_safety_report, validate_data_safety_lite). The 'lite' suffix is a clear modifier that maintains consistency.

    Tool Count4/5

    Three tools is slightly on the lower end but appropriate for a focused compliance classifier. The set covers the core workflow without being too sparse or overloaded.

    Completeness4/5

    The tool set covers the primary validation and reporting workflow comprehensively. Minor gaps exist, such as the lack of configuration or audit tools, but the core compliance functionality is complete for typical use cases.

  • Average 4.7/5 across 3 of 3 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 35 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.

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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

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are provided, so the description bears full responsibility. It discloses that payloads are analyzed in memory and immediately discarded, and it explains the consequences of not validating ('unrecoverable regulatory exposure'). It also states the verdict is machine-ready, though it does not detail required permissions or potential 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.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is front-loaded with the core purpose and then structured into usage timing, return values, and next steps. Each sentence adds value, though it is somewhat lengthy. It avoids redundancy with the schema and annotations.

    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 (multiple frameworks, multiple verdicts) and the presence of an output schema, the description is remarkably complete. It covers regulatory scope, return values, usage context, data handling policy, and escalation path. No important aspects are omitted.

    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 100%, providing baseline clarity. The description adds extra value by explaining how each parameter improves verdict accuracy (e.g., 'context improves verdict accuracy', 'payload never stored', 'data_origin_ip improves regulatory accuracy'). This goes beyond the schema descriptions.

    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 validates a data payload against multiple regulatory frameworks (GDPR, HIPAA, PCI-DSS, etc.), specifying the verb 'validates' and the resource 'data payload'. It distinguishes itself from siblings by mentioning the follow-up tool get_safety_report, indicating a distinct workflow.

    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 provides explicit when-to-use instructions: 'Call this BEFORE your agent passes any assembled payload to an external API... at the moment the payload is assembled'. It also guides the next step if the verdict is not SAFE_TO_PROCESS. However, it lacks explicit when-not-to-use scenarios or direct comparison with the 'lite' sibling.

    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 provided, so description carries full burden. It explains what the tool returns (regulation triggered, problematic fields, redaction strategy, compliant reformulation) and the consequences of not using it (unremediated violation, no audit trail).

    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?

    Several sentences but each adds value. Front-loaded with purpose, then usage guidelines, then outcomes. Could be slightly more concise, but no superfluous content.

    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 6 params (1 required), 100% schema coverage, and output schema exists, description fully covers when to use, what it returns, and consequences. No missing guidance.

    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 coverage is 100%, baseline 3. Description adds value by explaining workflow linking modes (REPORT, BATCH, AUDIT) to prior tool usage, though schema already documents enums. Extra context like 'immediately after validate_data_safety' goes beyond 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 the tool retrieves a 'detailed compliance report and remediation strategy' for a 'flagged payload'. It uses a specific verb ('Retrieves') and resource, and distinguishes from siblings by positioning it after 'validate_data_safety' returns non-SAFE verdicts.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Explicitly states when to call: after 'validate_data_safety' returns 'REDACT_BEFORE_PASSING, DO_NOT_STORE, or ESCALATE'. Warns against proceeding without it, providing clear context for use.

    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 provided, so description fully discloses behavioral traits: <100ms, no AI, no IP check, no jurisdiction lookup. Warns that SAFE_TO_PROCESS result can miss contextual PII and is not a full verdict.

    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?

    Slightly long but every sentence earns its place. Front-loaded with core purpose and usage. No fluff. Could be slightly tighter but still well-structured.

    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?

    Output schema exists, so return values not required but description mentions outputs SAFE_TO_PROCESS/REVIEW_REQUIRED. Also explains risk of false positives. Complete given complexity.

    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 coverage 100%, baseline 3. Description adds context for 'context' parameter and explains purpose of 'payload'. Adds value beyond schema descriptions.

    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?

    Clearly states tool validates payloads for sensitive patterns without AI classification. Distinguishes from sibling 'validate_data_safety' which presumably uses AI. Specific verb 'validate' and resource 'payload'.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Explicitly says when to use (pre-screening high-volume payloads when pattern detection sufficient) and when not (regulated environments). Directs to alternative validate_data_safety for flagged items.

    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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