MCP Vulnerability Checker Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose within the vulnerability domain: CVSS scoring, CVE lookup, EPSS scoring, exploit availability, VEX status, timeline tracking, package checking, and vulnerability search. No tools appear to overlap or cause confusion, as each targets a specific aspect of vulnerability assessment.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern (e.g., calculate_cvss_score, get_epss_score, search_vulnerabilities). The naming is uniform across the set, using descriptive verbs like 'calculate', 'get', 'check', and 'search' paired with clear nouns, making it easy to understand each tool's function.
Tool Count5/5
With 8 tools, the server is well-scoped for vulnerability checking, covering key areas like scoring, lookup, exploit assessment, and package analysis. Each tool earns its place by addressing a distinct need in the domain, avoiding both bloat and gaps in functionality.
Completeness5/5
The tool set provides comprehensive coverage for vulnerability assessment, including scoring (CVSS, EPSS), information retrieval (CVE lookup, timeline), exploit analysis, package checks, and search capabilities. There are no obvious gaps; it supports a full workflow from detection to prioritization.
Average 3.2/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
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This repository includes a README.md file.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
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  ]
}
```
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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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the data source (National Vulnerability Database) but doesn't cover critical aspects like rate limits, authentication requirements, error handling, or response format. This leaves significant gaps for an AI agent to understand operational constraints.
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 a single, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core purpose, making it easy to parse and understand quickly.
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?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., CVSS scores, descriptions) or behavioral traits like rate limits. For a lookup tool with no structured safety or output information, this leaves the AI agent under-informed.
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 schema description coverage is 100%, with the parameter 'cve_id' fully documented in the input schema. The description adds no additional parameter semantics beyond what's already in the schema, so it meets the baseline for adequate but unremarkable coverage.
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 the action ('Lookup') and resource ('CVE vulnerability information from the National Vulnerability Database'), making the tool's purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'search_vulnerabilities' or 'package_vulnerability_check', which prevents a perfect score.
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 provides no guidance on when to use this tool versus alternatives like 'search_vulnerabilities' or 'get_vulnerability_timeline'. It lacks context about prerequisites, such as needing a specific CVE ID format, or exclusions, like not being suitable for batch queries.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It states what the tool does but doesn't describe response format, error conditions, rate limits, authentication requirements, or whether this is a read-only operation. For a tool with no annotation coverage, this leaves significant behavioral gaps.
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 extremely concise at just 8 words, front-loading the core purpose without unnecessary elaboration. Every word earns its place - 'Check' (verb), 'VEX vulnerability status' (what), 'for specific products' (scope). There's zero waste or redundancy in this single-sentence description.
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?
For a tool with no annotations, no output schema, and 2 parameters, the description is insufficiently complete. It doesn't explain what VEX status entails, what format the response takes, whether this queries external databases, or what distinguishes VEX from other vulnerability assessments. Given the technical nature of vulnerability management and the lack of structured metadata, the description should provide more context.
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 schema already fully documents both parameters. The description doesn't add any parameter semantics beyond what's in the schema - it mentions CVE ID and product name but provides no additional context about format requirements, validation rules, or usage patterns. Baseline 3 is appropriate when schema does all the parameter documentation work.
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 the tool's purpose with a specific verb ('Check') and resource ('VEX vulnerability status for specific products'). It distinguishes from siblings like 'cve_lookup' or 'search_vulnerabilities' by focusing on VEX status rather than general vulnerability information. However, it doesn't explicitly differentiate from all siblings in the description text itself.
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 provides no guidance on when to use this tool versus alternatives like 'cve_lookup' or 'get_exploit_availability'. It mentions checking VEX status but doesn't explain when this is preferable to other vulnerability assessment tools. There's no mention of prerequisites, limitations, or specific contexts where this tool is most appropriate.
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, so the description carries the full burden of behavioral disclosure. It mentions what information is retrieved but doesn't cover critical aspects like whether this is a read-only operation, potential rate limits, authentication requirements, or the format of the returned data. This leaves significant gaps for an agent to understand how to interact with the tool effectively.
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 a single, efficient sentence that directly states the tool's purpose without any unnecessary words. It's front-loaded and easy to parse, making it highly concise and well-structured for quick understanding.
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?
Given the lack of annotations and output schema, the description is insufficient for a tool that retrieves detailed vulnerability information. It doesn't explain what the output looks like (e.g., timeline format, patch status details), nor does it address behavioral traits like data freshness or error handling, leaving the agent with incomplete context for proper usage.
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% description coverage, with the 'cve_id' parameter well-documented in the schema itself. The description doesn't add any meaningful information beyond what's already in the schema (e.g., it doesn't clarify parameter usage or constraints), so it meets the baseline score for high schema coverage without compensating value.
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 the tool's purpose with a specific verb ('Get') and resource ('vulnerability timeline and patch status information'), making it immediately understandable. However, it doesn't explicitly differentiate this tool from its siblings like 'cve_lookup' or 'search_vulnerabilities', which might also provide vulnerability information, so it doesn't reach the highest score.
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 provides no guidance on when to use this tool versus alternatives. With siblings like 'cve_lookup' and 'search_vulnerabilities' available, there's no indication of what makes this tool unique or when it should be preferred over others, leaving the agent to guess based on the name alone.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'advanced filtering' and 'comprehensive threat research,' but lacks critical details such as whether this is a read-only operation, if it requires authentication, rate limits, pagination behavior, or what databases it searches. This leaves significant gaps for safe and effective tool 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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action ('Search vulnerability databases') and qualifies it succinctly ('with advanced filtering'), making it easy to parse and understand quickly.
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?
Given the complexity of vulnerability searching, no annotations, and no output schema, the description is incomplete. It doesn't address key aspects like the scope of databases searched, result format, error handling, or performance considerations, which are essential for an agent to use this tool effectively in security contexts.
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 input schema already documents all three parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema, such as explaining interactions between filters or default behaviors. This meets the baseline for high schema coverage but doesn't enhance understanding.
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 the tool's purpose as 'Search vulnerability databases with advanced filtering,' which is a specific verb+resource combination. However, it doesn't explicitly distinguish this tool from its siblings like 'cve_lookup' or 'package_vulnerability_check,' which likely perform similar vulnerability-related searches with different scopes or methods.
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 provides no guidance on when to use this tool versus its siblings. It mentions 'advanced filtering' but doesn't specify scenarios where this is preferred over alternatives like 'cve_lookup' for direct CVE lookups or 'package_vulnerability_check' for package-specific checks, leaving the agent to guess based on context.
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?
With no annotations provided, the description carries full burden but only states the basic function without disclosing behavioral traits. It doesn't mention error handling for invalid vectors, rate limits, authentication needs, or what happens with unsupported CVSS versions. For a calculation tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves beyond the core calculation.
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 a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized for a simple calculation tool and front-loaded with the core functionality, making it easy to parse quickly.
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?
Given the tool's moderate complexity (single parameter calculation) with rich schema coverage but no output schema or annotations, the description is minimally adequate. It states what the tool does but doesn't explain return values, error cases, or integration context with sibling tools, leaving room for improvement in completeness.
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%, with the parameter 'vector' fully documented in the schema including format examples and version support. The description adds no additional parameter semantics beyond what the schema already provides, so it meets the baseline of 3 where the schema does the heavy lifting.
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 the verb 'calculate' and the resource 'CVSS base score from vector string', making the purpose immediately understandable. It distinguishes from siblings like 'get_epss_score' or 'cve_lookup' by focusing on score calculation rather than data retrieval. However, it doesn't specify the exact output format or differentiate from potential similar tools not in the sibling list.
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 provides no guidance on when to use this tool versus alternatives like 'get_epss_score' for exploit prediction or 'search_vulnerabilities' for broader vulnerability data. It mentions CVSS versions (v3.0 and v3.1) in the schema but not in the description itself, leaving usage context implied rather than explicit.
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, so the description carries the full burden. It mentions the tool returns 'AI-powered risk prioritization scores with percentile rankings', which adds some behavioral context, but it does not disclose other traits like rate limits, authentication needs, or error handling. The description is minimal and lacks comprehensive behavioral details.
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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and every part of the sentence contributes to understanding the tool's function.
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?
Given the tool has one parameter with full schema coverage and no output schema, the description is adequate but minimal. It explains what the tool does but lacks details on output format, error cases, or integration with sibling tools. For a simple lookup tool, it meets basic needs but could be more 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?
Schema description coverage is 100%, so the schema already documents the 'cve_id' parameter thoroughly. The description does not add any parameter-specific semantics beyond what the schema provides, such as format details or examples. Baseline score of 3 is appropriate as the schema handles parameter documentation.
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 specific action ('Get EPSS exploitability prediction score') and the resource ('for a CVE'), distinguishing it from sibling tools like 'calculate_cvss_score' or 'get_exploit_availability' by focusing on EPSS scores rather than CVSS or exploit availability.
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 assessing exploitation probability, but it does not explicitly state when to use this tool versus alternatives like 'calculate_cvss_score' or 'get_exploit_availability'. It provides some context (e.g., 'to assess the probability of exploitation') but lacks clear exclusions or named alternatives.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool checks for vulnerabilities using the OSV database, which implies a read-only, non-destructive operation, but does not detail rate limits, authentication needs, error handling, or response format. It adds some context but leaves significant behavioral aspects unspecified.
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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, with every part contributing essential 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?
Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits, output format, or integration with sibling tools, leaving gaps that could hinder effective use by an AI 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 schema already fully documents both parameters ('package_name' and 'version'). The description does not add any additional meaning beyond what the schema provides, such as examples or edge cases, resulting in a baseline score of 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 specific action ('Check for known vulnerabilities') and target resource ('Python packages using OSV database'), distinguishing it from siblings like 'cve_lookup' or 'search_vulnerabilities' by focusing on package-level vulnerability assessment rather than CVE-specific queries or broader searches.
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 Python packages but does not explicitly state when to use this tool versus alternatives like 'cve_lookup' for CVE details or 'search_vulnerabilities' for broader queries. It provides basic context but lacks explicit guidance on exclusions or comparisons with sibling tools.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adds context by listing sources (ExploitDB, Metasploit, GitHub, NVD) and return types (threat intelligence, exploitation indicators, weaponization status), but doesn't cover aspects like rate limits, authentication needs, or potential errors. It doesn't contradict annotations, as none exist.
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 a single, efficient sentence that front-loads the core purpose ('Check for public exploits and PoCs for a CVE') with no wasted words. Every part of the sentence contributes essential information, making it highly concise and well-structured.
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?
Given the tool's complexity (threat intelligence query), no annotations, and no output schema, the description is moderately complete. It covers purpose, sources, and return types, but lacks details on output format, error handling, or integration with sibling tools, leaving some gaps for an agent to infer behavior.
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 input schema already fully documents the 'cve_id' parameter with format details and purpose. The description adds no additional parameter semantics beyond what's in the schema, meeting the baseline score of 3 for high coverage without extra value.
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 with specific verbs ('check for public exploits and PoCs') and resources ('for a CVE'), distinguishing it from siblings like 'cve_lookup' (general info) or 'get_epss_score' (exploit prediction). It precisely defines what the tool does without being vague or tautological.
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 implies usage context by specifying 'check for public exploits and PoCs for a CVE,' suggesting it's for threat intelligence and risk assessment. However, it lacks explicit guidance on when to use this tool versus alternatives like 'search_vulnerabilities' or 'get_vex_status,' which could help differentiate further.
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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