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Patrowl

PatrowlIntelMCP

Official
by Patrowl
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v0.0.1

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: get_cve retrieves full details for a single CVE, list_trending_attacks shows trending threats, and search_cves provides filtered search. No ambiguity between them.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun snake_case pattern (get_cve, list_trending_attacks, search_cves), making them predictable and easy to understand.

    Tool Count5/5

    Three tools is appropriate for a focused threat intelligence server. Each tool serves a distinct, essential function (detail retrieval, trending list, search) without being too few or too many.

    Completeness4/5

    The tool set covers the core needs: fetching CVE details, searching with filters, and viewing trending threats. Minor gaps exist, such as lacking a direct tool for bulk listing or subscription features, but the set is largely complete for typical use cases.

  • Average 4.1/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 4 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.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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 carries the full burden. It clearly describes what data is fetched (CVSS, EPSS, etc.), conveying a read-only intent. However, it does not mention potential side effects, rate limits, or authentication requirements, though such transparency is less critical for a simple fetch operation.

    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?

    A single sentence that front-loads the purpose and lists key data items. Every phrase adds value, with no extraneous 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?

    Without an output schema, the description serves as the output specification. It lists multiple data fields (CVSS, EPSS, etc.), which is sufficient. Minor gaps include no mention of response size or pagination (not needed for a single CVE), and no explicit note about error handling for invalid CVE IDs.

    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 covers 100% of parameters with descriptions. The description adds global context but does not enhance parameter meaning beyond the schema. No additional format or constraint details are given for the required cve_id or optional verbose.

    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 that the tool fetches full intelligence for a single CVE, listing specific data points like CVSS, EPSS, CISA KEV status, etc. This distinguishes it from sibling tools like search_cves which presumably handles multiple CVEs, and list_trending_attacks which focuses on trending attacks rather than individual CVEs.

    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 fetching data on a single CVE, but does not explicitly state when to use this tool versus alternatives (e.g., search_cves for bulk or list_trending_attacks for trending). No when-not or exclusion criteria are provided.

    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?

    No annotations provided, so description carries full burden. It discloses ordering and suggests parameter usage, but lacks explicit mention of read-only nature, rate limits, pagination, or what 'trending' means. Adequate but not thorough.

    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?

    Two sentences, no fluff. Purpose is front-loaded, followed by a useful usage hint. Every sentence earns its place.

    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 output schema and no annotations, the description covers the tool's purpose, ordering, and a key parameter hint. It is sufficient for a list tool, though it could mention return type for completeness.

    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%, with all parameters described in the schema. The description adds value by providing an example usage (min_severity=3) beyond what the schema offers, justifying a score above baseline 3.

    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 verb 'list', the resource 'trending attacks from the Patrowl feed', and the ordering 'most recent first'. It distinguishes from sibling tools (get_cve, search_cves) which are about CVEs.

    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 a specific usage hint for min_severity=3 to focus on High and Critical. Does not explicitly state when to use this tool vs alternatives, but the context implies it's for trending attacks while siblings are for CVEs.

    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?

    No annotations provided, so description carries full burden. It implies a read operation (search) but does not explicitly state read-only, no side effects, or disclose rate limits or authentication needs. The mention of 'compact, ranked results' adds some behavioral context, but more specifics would be beneficial.

    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?

    Two sentences, front-loaded with purpose, efficient use of words. No fluff.

    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 output schema and no annotations, the description covers the tool's purpose, use cases, and relationship to siblings. Could mention output format or pagination but overall complete for a search 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 coverage is 100%, so all parameters are documented. The description does not add extra meaning beyond the schema, which is acceptable. Baseline score of 3 is appropriate as the schema carries the load.

    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 searches the PatrowlIntel CVE feed with rich filters, returning compact ranked results. It distinguishes from the sibling 'get_cve' by indicating that for full records one should use that tool.

    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 provides use cases: triage by risk, surface KEV/exploited CVEs, scope vendor/technology, and instructs to follow up with get_cve for full records. This gives clear when-to-use and when-not-to-use 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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Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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