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vivekanjana76

azure-compliance-mcp

by vivekanjana76
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a distinct purpose: check_compliance evaluates specific security controls, get_patch_status reports VM patch posture, and query_resources performs generic read-only queries. No overlap in functionality.

    Naming Consistency5/5

    All tool names use lowercase with underscores and follow a clear verb_noun pattern (check_compliance, get_patch_status, query_resources), providing a predictable and consistent naming scheme.

    Tool Count4/5

    With only 3 tools, the server is tightly focused on Azure compliance and resource queries. While the count is somewhat minimal, each tool is well-justified and covers the core use cases without being overloaded.

    Completeness4/5

    The tool set covers compliance evaluation, patch status, and generic resource queries, which together address a broad range of compliance workflows. The generic query tool compensates for potential gaps, though some specialized compliance checks might be missing.

  • Average 4/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 22 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

  • Behavior2/5

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

    No annotations are provided, so the description carries full burden. It reveals read-only behavior and ARG output shape, but does not disclose permissions, rate limits, or other behavioral traits.

    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?

    Three clear, non-redundant sentences: purpose, filter behavior, output format. Front-loaded with no wasted words.

    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 presence of an output schema and no required parameters, the description covers essential behavior concisely. Minor gap: no mention of pagination or order, but limit parameter addresses row count.

    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%, so parameters are already documented. The description adds the AND combination behavior, which is valuable but does not elaborate on parameter meaning beyond what the schema provides.

    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 uses specific verb 'look up' and resource 'resources', along with 'structured, read-only filters', clearly distinguishing it from sibling tools (check_compliance, get_patch_status) which serve different purposes.

    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 states filters are combined with AND, providing usage context, but lacks explicit guidance on when to use versus alternatives or when not to 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?

    With no annotations provided, the description bears full responsibility for behavioral transparency. It fully discloses traits: honest provenance, 'not_evaluable' for missing data, partial coverage of 'disk_encryption', and specific details about 'guest_config_extension'. It sets accurate expectations about limits and data sources.

    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 fairly concise for the complexity, front-loading the main purpose and then efficiently explaining key behavioral notes. Every sentence adds value, though it could be slightly sharper (e.g., avoid repeating 'not_evaluable' multiple times).

    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 complexity (4 parameters, 5 controls, output schema), the description covers essential behavioral aspects and edge cases (e.g., partial controls, provenance). It doesn't detail the output schema fields or all response formats, but those are handled by the output schema. The description is sufficiently complete for an agent.

    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%, so the baseline is 3. The description adds minimal value beyond the schema for parameters; it focuses on general behavior rather than enriching parameter meanings. The provenance detail pertains to output, not input semantics.

    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's purpose: 'Evaluate named security/governance controls and report where each verdict came from.' It uses a specific verb ('evaluate') and resource ('controls'), and the mention of provenance distinguishes it from typical compliance tools. Siblings are different (patch status, query resources), and this description uniquely defines its scope.

    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 usage for compliance checks and provides details on control behaviors, but it does not explicitly state when to use this tool over siblings like 'query_resources' or 'get_patch_status'. No direct guidance on when not to use it or alternatives is given.

    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, the description fully handles transparency. It explains the data provenance (source='arg' from patchassessmentresources table), defines the not_evaluable state for deallocated/stopped VMs, and clarifies that pendingUpdateCount is null (unknown) rather than zero. This goes well beyond a typical description.

    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 a clear opening sentence, followed by important caveats. It is concise without extraneous information, though it could be slightly more compact.

    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 presence of an output schema, the description does not need to explain return values. It covers edge cases (not_evaluable), provenance, and parameter defaults. The tool is fully described for its intended use.

    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%, so baseline is 3. The description adds some context (e.g., default status_filter returns pending, excludes not_evaluable), but the schema already provides detailed descriptions for each parameter. No significant additional meaning is provided.

    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 'Report per-VM patch/update posture from Azure Resource Graph patch assessments.' It provides a specific verb (report) and resource (per-VM patch/update posture), and distinguishes from siblings like check_compliance and query_resources by focusing on patch assessment data.

    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 usage for checking patch posture but does not explicitly state when to use this tool over its siblings (check_compliance, query_resources). No when-not-to-use or alternative guidance is provided.

    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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