Malicious URLs MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: get_random retrieves a single random URL, list_urls fetches a paginated list of all URLs, and search allows querying by URL. There is no overlap in functionality, making it easy for an agent to select the right tool.
Naming Consistency4/5The tool names follow a consistent verb-based pattern (get_random, list_urls, search), with all using snake_case. However, 'search' deviates slightly by not including a noun, which is a minor inconsistency in an otherwise predictable naming scheme.
Tool Count3/5With only 3 tools, the server feels thin for handling malicious URLs, as it lacks operations like adding, updating, or deleting URLs, or more advanced analysis features. While the tools cover basic retrieval, the scope seems limited for a domain that might benefit from more comprehensive management.
Completeness2/5The tool surface is significantly incomplete for a malicious URL server, as it only provides read operations (random, list, search) with no ability to create, update, delete, or analyze URLs. This leaves obvious gaps in CRUD coverage and limits agents to passive querying without active management capabilities.
Average 2.7/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 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
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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
- Behavior1/5
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 fails completely. 'Search by url' doesn't indicate whether this is a read-only operation, what kind of data it returns, whether it has rate limits, authentication requirements, or any side effects. For a search tool with zero annotation coverage, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just three words with zero wasted language. It's front-loaded with the core action and immediately specifies the key parameter. While under-specified, it achieves maximum efficiency within its limited scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's apparent simplicity (1 parameter, no annotations, no output schema), the description is still incomplete. It doesn't explain what the search returns, what it searches through, or how results are presented. For even a basic search tool, more context about the operation's scope and output is needed for proper agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100% with the single parameter 'url' documented as 'Example value: google.com'. The description 'Search by url' adds minimal semantic context beyond the schema, confirming the parameter's role but not elaborating on format expectations or search behavior. With high schema coverage, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Search by url' is a tautology that essentially restates the tool name 'search' with minimal elaboration. It specifies the verb 'search' and mentions 'url' as the resource, but doesn't explain what kind of search this performs or what it searches through. Compared to sibling tools like 'get_random' and 'list_urls', it doesn't clearly differentiate its specific purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. There's no mention of context, prerequisites, or comparisons to sibling tools like 'get_random' or 'list_urls'. The agent receives no help in determining whether this is the appropriate tool for a given search scenario.
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 offers minimal behavioral insight. It mentions pagination, implying a list operation that might return partial results, but doesn't disclose whether this is read-only, has rate limits, requires authentication, what happens on invalid page numbers, or the format/scope of returned URLs. For a tool with zero annotation coverage, this leaves critical behavioral traits unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point without unnecessary words. It's appropriately sized for a simple tool, though it could be more front-loaded with key details like the resource type. There's no wasted verbiage, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter, no output schema, no annotations), the description is incomplete. It doesn't explain what 'urls' refers to, the pagination mechanism, or what the output looks like (e.g., list format, error handling). Without annotations or output schema, the description should compensate more to help an agent use the tool correctly, but it leaves too many gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'page' documented in the schema as a string with an empty example. The description adds that this is for pagination ('with page number'), which provides some context beyond the schema, but doesn't explain the pagination system (e.g., starting page, format, what 'page' represents). Since schema coverage is high, the baseline is 3, and the description adds marginal value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action ('Get list') and resource ('all urls'), but is vague about scope and lacks sibling differentiation. It doesn't specify what kind of URLs these are (e.g., from a database, web pages, API endpoints) or how 'all urls' relates to pagination. Compared to siblings 'get_random' and 'search', it doesn't clarify when this tool is preferred over those alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus the sibling tools 'get_random' or 'search'. The description mentions pagination ('with page number'), but doesn't explain whether this is for browsing all URLs systematically versus using search for filtering or get_random for sampling. There's no context about prerequisites, limitations, or typical use cases.
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 states the tool 'responds with one random url', which implies a read-only operation, but doesn't specify source constraints (e.g., from a predefined set, database, or API), randomness characteristics (e.g., uniform distribution, seed), or response format details. This leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is 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 any fluff or redundant information. It's front-loaded with the core action and resource, making it highly concise and well-structured for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimal but insufficient. It doesn't explain what 'random' entails (e.g., selection method, source), the format of the returned URL, or any error conditions. For a tool with no structured data to rely on, more context is needed to ensure proper usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, and since there are none, it doesn't need to compensate for any gaps. A baseline of 4 is justified as the description focuses on the tool's purpose without unnecessary parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('responds with') and resource ('one random url'), making the purpose immediately understandable. It doesn't differentiate from siblings like 'list_urls' or 'search', but it's specific enough to understand what the tool does without being tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'list_urls' or 'search'. It doesn't mention scenarios where random selection is preferred over listing or searching, nor does it indicate any prerequisites or exclusions for usage.
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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