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zoomeye-ai

ZoomEye MCP Server

Official
by zoomeye-ai
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Python
Hybrid

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool serves a distinct purpose: one for general asset search, one for vulnerability detail by ID, and one for vulnerability keyword search. There is no overlap in functionality.

    Naming Consistency5/5

    All tools follow a consistent 'zoomeye_' prefix with snake_case naming: search, vuldb_by_id, vuldb_by_keyword. Pattern is uniform and predictable.

    Tool Count4/5

    With 3 tools, the set is minimal but appropriate for the ZoomEye domain, covering asset search and vulnerability queries. Slightly thin but reasonable given the focused scope.

    Completeness3/5

    The tools cover basic search and vulnerability lookup, but lack features like retrieving detailed host info, filtering by specific fields, or obtaining result counts. Some operations are missing for full workflow coverage.

  • Average 3.2/5 across 3 of 3 tools scored. Lowest: 2.6/5.

    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
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

  • 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

  • Behavior2/5

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

    With no annotations provided, the description must fully disclose behavioral traits. It indicates a read-only operation (search/retrieve), but fails to describe output format, pagination, rate limits, or any side effects. The abrupt end ('Results include:') leaves the agent guessing what the tool returns, which is a significant gap for transparency.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness2/5

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

    The description is short, but it is incomplete, ending with 'Results include:' without any continuation. This disrupts the structure and leaves the description unfinished. Every sentence should be complete and purposeful, and this one fails to deliver its intended content.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness1/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given no output schema, the description should explain the return values comprehensively. It starts listing results but cuts off, providing zero information about what the formatted results contain. This is a major omission for a tool that only has one parameter and no other documentation.

    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 has 100% coverage, with the parameter 'cve_id' described and examples given. The description repeats this information without adding substantial new meaning. Baseline is 3, and since no extra semantics are provided, the score remains at 3.

    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 clearly states 'Search for detailed vulnerability information by vulnerability ID', specifying the verb and resource. It lists the accepted ID formats (CVE, CNVD, CNNVD), which helps the agent understand the tool's scope. However, it does not differentiate from sibling tools like 'zoomeye_search' or 'zoomeye_vuldb_by_keyword', and the incomplete sentence 'Results include:' slightly reduces clarity.

    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 says 'Use this tool to retrieve...' but provides no guidance on when to use it versus alternatives, such as the sibling tool 'zoomeye_vuldb_by_keyword'. There is no mention of prerequisites, limitations, or exclusions, leaving the agent to infer usage context without explicit advice.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior4/5

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

    With no annotations, the description carries full burden. It thoroughly explains search behavior (case-insensitivity, exact matching, operators, scopes), but omits details on rate limits, authentication, or side effects. For a read-like search tool, it is largely transparent.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness1/5

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

    The description is extremely long (multiple paragraphs of syntax manual), which is not concise. It lacks front-loading of key information and would overwhelm an AI agent.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Despite detailed search syntax, the description lacks information on return format, pagination behavior beyond parameters, error handling, and output interpretation. With a complex tool and no output schema, more context is needed.

    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 search syntax knowledge but does not provide additional meaning for the parameters themselves (e.g., how to construct qbase64 or interpret fields).

    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 searches for devices and websites on ZoomEye, and provides extensive search syntax. It distinguishes itself from sibling tools (vuldb tools) by focusing on asset search.

    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 includes many search examples and syntax rules, implying usage scenarios, but it does not explicitly state when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

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

    No annotations are provided, but the description only lists output fields without behavioral disclosures like read-only guarantee, rate limits, or authentication needs.

    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 concise and front-loaded, though the second paragraph could be shortened without losing value.

    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, the description reasonably explains return fields (CVE, severity, etc.) and implies pagination via page_size, though total count is 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 coverage is 100%, and the description enhances understanding by providing examples for keyword and clarifying page_size defaults/maximum.

    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 searches ZoomEye's vulnerability database by keyword, and implicitly distinguishes it from siblings (search vs. by ID).

    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 explains it retrieves vulnerability info for products/vendors but does not explicitly compare with zoomeye_search or zoomeye_vuldb_by_id.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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