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ofershap

mcp-server-dns

by ofershap

Server Quality Checklist

67%
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  • Latest release: v1.0.0

  • Disambiguation4/5

    The tools are mostly distinct with clear purposes: dns_lookup for specific record types, resolve_all for common records in bulk, reverse_dns for PTR lookups, and whois for domain registration data. However, check_nameservers overlaps with dns_lookup (which can also return NS records) and resolve_all (which includes NS), potentially causing confusion in tool selection.

    Naming Consistency4/5

    The naming follows a consistent snake_case pattern with descriptive verb-noun combinations (e.g., dns_lookup, reverse_dns). Minor deviations exist: check_nameservers uses 'check' while others use more specific verbs like 'lookup' or 'resolve', but overall the convention is readable and predictable.

    Tool Count5/5

    With 5 tools, this server is well-scoped for DNS operations. Each tool serves a distinct function in the domain, and the count is neither too sparse nor bloated, making it manageable for agents to handle typical DNS-related tasks effectively.

    Completeness4/5

    The toolset covers essential DNS operations: lookup, bulk resolution, reverse lookups, and WHOIS queries. A minor gap exists in lacking explicit tools for DNS record management (e.g., create or update records), but this is reasonable if the server is focused on querying rather than administration, and agents can still perform core diagnostic tasks.

  • Average 3.3/5 across 5 of 5 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
  • 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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't mention any behavioral traits such as rate limits, authentication needs, error handling, or what the output looks like (e.g., format, structure). This leaves significant gaps for a tool that performs network operations.

    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, clear sentence that directly states the tool's purpose without any unnecessary words. It is front-loaded and efficiently communicates the core function, making it easy for an agent to parse 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 for a tool that retrieves network data. It doesn't explain what the output contains (e.g., list of nameservers, error responses) or address potential complexities like handling invalid domains or network timeouts, which are important for an agent to use it correctly.

    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 'domain' parameter well-documented in the schema itself. The description adds no additional meaning beyond what the schema provides (e.g., it doesn't clarify edge cases or provide examples beyond the schema's 'e.g. example.com'), so it meets the baseline score when schema coverage is high.

    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 ('Get') and resource ('nameserver (NS) records for a domain'), making the purpose immediately understandable. It doesn't explicitly distinguish from siblings like 'dns_lookup' or 'resolve_all', which might also retrieve DNS-related data, so it misses the highest score for sibling differentiation.

    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 'dns_lookup' or 'whois' from the sibling list. It lacks context about specific use cases, exclusions, or prerequisites, leaving the agent to infer usage based on the tool 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 the return types ('Returns A, AAAA, MX... records') but lacks critical details like whether this is a read-only operation, potential rate limits, authentication needs, error conditions, or how results are formatted. For a tool with no annotation coverage, this leaves significant gaps.

    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 appropriately concise with two sentences that directly state the tool's function and return values. It's front-loaded with the core purpose, though it could be slightly more structured by separating usage notes from behavioral details.

    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 no annotations and no output schema, the description is incomplete for a tool with two parameters. It doesn't explain the return format, error handling, or behavioral constraints, leaving the agent with insufficient context to use the tool effectively beyond basic parameter passing.

    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 ('domain' and 'type'). The description adds no additional parameter semantics beyond what's in the schema—it merely restates the enum values for 'type'. This meets the baseline for high schema 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 tool's purpose: 'Look up DNS records for a domain.' It specifies the verb ('look up') and resource ('DNS records'), making the function immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'check_nameservers' or 'resolve_all', which likely have overlapping DNS-related functionality.

    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. It doesn't mention sibling tools like 'check_nameservers' or 'resolve_all', nor does it specify scenarios where this tool is preferred or excluded. Usage is implied by the function but lacks explicit 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 offers minimal behavioral context. It doesn't disclose rate limits, error conditions (e.g., invalid IP formats, non-existent PTR records), authentication needs, or what the output contains (e.g., hostname, multiple records). The description only states the basic operation without 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?

    The description is a single, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it easy to parse. Every word earns its place without redundancy.

    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?

    For a simple lookup tool with one parameter and no output schema, the description is minimally complete but lacks context about output format or error handling. It covers the basic purpose but doesn't help the agent understand what to expect from the operation, leaving gaps in usability.

    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 'ip' parameter fully documented in the schema. The description adds no additional meaning beyond what's in the schema (e.g., no examples of IPv6, no note about private IPs). Baseline 3 is appropriate since the schema does the heavy lifting.

    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 ('Perform a reverse DNS (PTR) lookup') and the resource ('on an IP address'), distinguishing it from sibling tools like 'dns_lookup' (which likely does forward lookups) and 'whois' (which provides domain registration info). The inclusion of '(PTR)' adds technical precision.

    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 'dns_lookup' or 'resolve_all'. It doesn't mention use cases (e.g., verifying IP ownership, troubleshooting) or exclusions (e.g., not for domain names). The agent must infer usage from the tool 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 full burden for behavioral disclosure. It mentions the technical approach (IANA, referrals) but doesn't cover important behavioral aspects like rate limits, authentication needs, error handling, or what the response format looks like. For a tool with no annotations, this leaves significant 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 (two sentences) with zero wasted words. It's front-loaded with the core purpose and follows with technical implementation details, making every sentence earn its place.

    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 no annotations and no output schema, the description should provide more complete context for this network query tool. It lacks information about response format, error conditions, rate limits, or what specific WHOIS data fields are returned. The technical implementation details are helpful but insufficient for full contextual understanding.

    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%, so the schema already documents the single 'domain' parameter completely. The description doesn't add any parameter-specific information beyond what's in the schema, maintaining the baseline score for high schema coverage.

    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 ('Query WHOIS data') and resource ('for a domain'), distinguishing it from sibling tools like DNS lookup or nameserver checks. It provides technical detail about using IANA and following referrals, which adds specificity beyond a generic query.

    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 context through technical details (IANA, registrar referrals) but doesn't explicitly state when to use this tool versus alternatives like DNS lookup or nameserver checks. No explicit exclusions or comparisons to sibling tools 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 are provided, so the description carries the full burden. It discloses the batch behavior ('resolve all... in one call') and lists record types, but does not mention potential limitations like rate limits, error handling, or output format. It adds some behavioral context but lacks completeness for a tool with no annotations.

    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 key information (action, resource, scope) with zero waste. Every word contributes to clarity without redundancy.

    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 no annotations, no output schema, and a simple input schema, the description is adequate but has gaps. It covers purpose and scope well, but lacks details on behavioral traits (e.g., performance, errors) and output, making it minimally viable but not fully complete for informed 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%, with the single parameter 'domain' well-documented in the schema. The description does not add meaning beyond what the schema provides (e.g., no extra constraints or examples), so it meets the baseline of 3 when schema coverage is high.

    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 ('resolve all common DNS record types') and the resource ('for a domain'), distinguishing it from sibling tools like 'dns_lookup' (likely more general) and 'reverse_dns' (different direction). It explicitly lists the record types (A, AAAA, MX, TXT, NS, CNAME) to specify scope.

    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 ('in one call') for batch resolution, but does not explicitly state when to use this tool versus alternatives like 'dns_lookup' or 'check_nameservers'. It provides clear intent but lacks explicit comparison or exclusion 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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