NIS2 Compliance MCP

Server Quality Checklist

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Latest release: v1.2.4
Disambiguation5/5
Each tool addresses a distinct compliance aspect: scope classification, incident classification, auditing, listing measures, enforcement tracking, certificate generation, and management accountability. No two tools have overlapping purposes.
Naming Consistency3/5
Names mix verb_noun patterns (audit_article_21, classify_entity) with noun_phrases (enforcement_status, management_body_checklist) and get_ prefix (get_nis2_certificate). While mostly understandable, the inconsistency reduces predictability.
Tool Count5/5
Seven tools cover the key NIS2 compliance tasks without bloat. The count is well-scoped for a focused compliance assessment server.
Completeness4/5
Core compliance workflows are covered (scoping, incident classification, auditing, listing, enforcement, certification, management accountability). Missing remediation guidance or supply chain checks, but no critical dead ends.
Average 4.3/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 51 commits in the last 12 weeks
- Last stable release on May 7, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
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

Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden and excels: discloses read-only nature, authentication requirements, rate limits per tier, error handling, idempotency, and data privacy. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear sections, but contains redundancy (e.g., 'Behavior' line repeats later 'Behavioral Transparency' details). Slightly verbose for the amount of unique information.
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?
Covers behavioral aspects thoroughly but lacks detail on output format or semantics of parameters (entity_name, overall_score). Output schema exists but description doesn't hint at certificate structure.
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%, yet the description's 'Args' only restates parameter names and types without adding meaning (e.g., format, constraints, examples). This fails to compensate for the sparse 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 it generates a timestamped signed NIS2 compliance certificate, specifying the resource and action. It is distinct from sibling tools which audit, classify, or list, making purpose unambiguous.
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?
Provides explicit 'When to use' and 'When NOT to use' sections, covering appropriate contexts like gap analysis and warning against legal substitution. Lacks direct comparison to siblings but is sufficient for differentiation.
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?
With no annotations provided, the description carries the full burden and fully discloses all relevant behaviors: read-only, stateless, idempotent, rate limits (10/day free), authentication needs (none for basic), error handling, and data privacy. This exceeds requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with sections but contains redundancy, notably the 'Behavior' and 'Behavioral Transparency' sections that repeat the same points (read-only, idempotent). This could be condensed without losing information.
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?
The tool has moderate complexity (auditing against NIS2) and an output schema is indicated. The description covers return values (evidence status, gaps, sanction tier), usage guidance, and behavior. However, parameter descriptions are vague, and with 3 parameters (1 required), more specific guidance on entity_description and current_controls would improve completeness.
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%, so description must compensate. However, the 'Args' section only restates parameter names and types generically (e.g., 'The entity description to analyze') without explaining expected formats, examples, or constraints. This adds little value beyond the 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 audits controls against NIS2 Article 21's 10 measures. The verb 'audit' and resource 'controls against NIS2 Article 21 measures' are specific, and sibling tools like classify_entity or enforce_status have different purposes, making this distinct.
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' (assessment, gap analysis) and 'When NOT to use' (not legal advice) sections, offering clear context. However, it does not explicitly contrast with sibling tools like classify_entity or list_article_21_measures, which could further guide selection.
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, but the description covers side effects (read-only, stateless), authentication (no auth for basic, API key for pro), rate limits (free 10/day), error handling, idempotency, and data privacy. Very thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with clear sections, but contains redundancy (e.g., 'Behavioral Transparency' repeated). Some sentences could be merged for better conciseness.
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?
Covers size-cap rules, rate limits, auth, and error handling. With an output schema present, return values are not needed. Lacks clarity on possible sector values, but overall adequate for agent 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?
Schema has 0% description coverage. The 'Args' section adds generic phrases like 'to analyze or process' that barely clarify meaning. Although the main description mentions size-cap rules, parameter-specific semantics are weak.
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 classifies an entity's NIS2 scope (essential/important/out-of-scope) and sector, with specific rules. It distinguishes from siblings like classify_incident by focusing on entity classification.
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?
Explicit 'When to use' and 'When NOT to use' sections provide context for gap analysis and compliance checks, and warn against legal advice. However, it does not contrast with sibling tools or specify when to prefer alternatives.
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?
With no annotations provided, the description carries full burden. It includes a dedicated 'Behavioral Transparency' section covering side effects (read-only, no side effects), authentication, rate limits, error handling, idempotency, and data privacy. This is comprehensive and fully informs 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 well-structured with clear sections and front-loaded purpose. However, there is slight redundancy between the initial 'Behavior' paragraph and the later 'Behavioral Transparency' section, which could be merged for conciseness.
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 output schema exists, the description needn't detail return values. It covers input, behavior, usage, and limitations. Lacks only deeper context about the checklist content, but overall sufficient for agent selection and invocation.
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 has 0% description coverage for its only parameter (api_key). The description merely repeats 'api key to analyze or process', adding minimal value. It fails to explain the key's purpose, source, or format, which is insufficient for a parameter with no schema description.
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 provides a checklist for NIS2 Article 20 management body accountability, using a specific verb ('assess, audit, verify'). It distinguishes itself from sibling tools like audit_article_21 and classify_entity by focusing on this specific compliance aspect.
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 explicitly states when to use (gap analysis, compliance documentation) and when not to use (substitute for legal counsel). However, it does not mention when to prefer this over specific siblings, missing a chance for clearer differentiation.
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?
Despite no annotations, the description comprehensively covers read-only, stateless, idempotent nature, authentication requirements, rate limits, error handling, and data privacy. No contradictions with annotations.
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 well-structured with clear sections (behavior, usage, args, transparency) and front-loaded purpose. However, the arg descriptions are repetitive, slightly reducing conciseness.
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 no annotations and an output schema present, the description covers behavior, authentication, rate limits, and error handling well. The output format (returning 'significant' status and triggers) is implied but not fully explicit.
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?
With 0% schema description coverage, the arg descriptions are generic ('The X to analyze or process'), adding minimal meaning beyond parameter names and types. They fail to explain how each parameter influences classification.
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 classifies cyber incidents against NIS2 Article 23 thresholds and specifies the 'significant' output triggering regulatory timelines. It distinguishes from sibling tools like 'classify_entity' or 'audit_article_21' by its incident-specific focus.
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?
The description includes explicit 'When to use' (gap analysis, compliance checks) and 'When NOT to use' (not legal advice) sections, providing clear context and differentiation from alternatives.
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?
Despite no annotations, the description thoroughly discloses side effects (none), authentication requirements, rate limits, error handling, idempotency, and data privacy, exceeding basic expectations.
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?
Well-structured with clear sections, but somewhat verbose. Could be shortened without losing clarity.
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?
Covers all necessary aspects given the tool's simplicity: behavior, when to use, side effects, error handling, and output schema exists. Very complete.
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 description adds little beyond the schema for the only parameter (api_key), mentioning it in the Args section but without additional detail. With 0% schema description coverage, more guidance would be beneficial.
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 provides 'Current NIS2 enforcement status + national transposition tracker' and lists specific use cases like gap analysis and readiness checks, distinguishing it from sibling tools.
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 use (assess, audit, verify compliance) and when NOT to use (not a substitute for legal counsel). Provides clear context for usage.
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?
With no annotations provided, the description fully discloses behavioral traits: read-only, stateless, idempotent, rate limits, authentication requirements, error handling, and data privacy. This exceeds the minimum needed for safe invocation.
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 well-structured with clear sections (Behavior, When to use, etc.), front-loads the main purpose, and every sentence adds value. It is appropriately sized for the detail provided.
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 simplicity (one optional parameter, output schema exists), the description covers purpose, usage, behavior, authentication, rate limits, and error handling comprehensively. It meets all needs for correct invocation.
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 description mentions the api_key parameter as 'The api key to analyze or process,' but this is vague and does not clarify its actual role (e.g., for rate limiting or authentication). The behavioral transparency section explains authentication separately, creating confusion. Given 0% schema coverage, the description should provide clearer parameter meaning.
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 lists all 10 cybersecurity risk-management measures under NIS2 Article 21, using a specific verb and resource. It distinguishes itself from siblings like audit_article_21 or classify_entity by focusing on listing measures.
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?
The description includes explicit 'When to use' and 'When NOT to use' sections, providing context for compliance assessment and gap analysis while warning against substituting for legal counsel. This gives clear guidance on appropriate usage scenarios.
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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