WolfTech DNS MCP Server

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct DNS resource or check: generic lookup, SPF, MX, DMARC, DKIM, reverse DNS, and aggregate health. No two tools overlap in purpose.
Naming Consistency4/5
All names are lowercase snake_case and readable, but they mix patterns: 'dns_lookup' and 'reverse_dns' use different structures than the '_check' suffix used by most email validation tools. Minor inconsistency, still predictable.
Tool Count5/5
Seven tools is well-scoped for a DNS/email diagnostic server. Each tool addresses a specific need, and the count feels appropriately focused without bloat or thinness.
Completeness5/5
The set covers generic DNS lookups, core email authentication records (SPF, MX, DMARC, DKIM), reverse DNS, and an aggregate health check. It provides a complete read-only diagnostic workflow with no obvious gaps.
Average 4.1/5 across 7 of 7 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 status not available
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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?
The description provides minimal behavioral information beyond the operation itself. It mentions input formats and default DNS server, but does not disclose whether it is read-only, error behavior, timeout, or return characteristics. Since no annotations are provided, the description fails to carry the burden of behavioral transparency.
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, front-loaded with the purpose, followed by concise parameter bullets. Every sentence adds value 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 the tool's simplicity and the presence of an output schema, the description covers the main input semantics. However, it lacks usage guidelines and behavioral details such as error handling or read-only status, making it incomplete for a fully self-sufficient description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions for properties (0% coverage), and the description effectively compensates by explaining each parameter, including an example for ip_address and the default for dns_server. This adds meaningful semantic value beyond the schema.
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 explicitly states 'Perform a reverse DNS lookup on an IP address,' clearly identifying the verb and resource. It does not explicitly contrast with sibling tools like dns_lookup, but the reverse nature is clear from the name and description.
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?
No explicit guidance is given on when to use this tool versus alternatives such as dns_lookup. The intended use case is implied by the tool's name and description, but there are no exclusions or alternative recommendations 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?
With no annotations provided, the description carries the full burden for behavioral disclosure. It adds useful detail about output (priority ordering, resolved IPs) and the configurable DNS server default, but it does not explicitly state that the tool is read-only or non-destructive, nor does it mention any failure modes or prerequisites. Some transparency exists but gaps remain.
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 two sentences: a clear purpose statement followed by a compact parameter listing. No wasted words, front-loaded with the main verb and resource. It is appropriately sized for a simple, focused tool.
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?
For a simple DNS lookup tool with an output schema (not shown but present), the description covers the core functionality and all parameters. It lacks explicit usage scenarios or limitations, but given the straightforward nature of the tool and the presence of an output schema, the description is nearly complete. A small deduction because there is no mention of edge cases (e.g., nonexistent domain, timeout) or expected output format beyond the schema.
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?
The input schema provides only types and a default for dns_server, with no descriptions. The description compensates by explaining each parameter with a concrete example for domain and clarifying the default behavior for dns_server. This adds meaning beyond the schema, though for a simple two-parameter tool it does not need to do much more.
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 uses a specific verb ('Look up') and a clear resource ('MX records'), and adds scope ('with priority ordering and resolved IP addresses'). This distinguishes it from siblings like dns_lookup, spf_check, and dmarc_check, which target other DNS record types or checks.
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 use for MX record lookups but does not explicitly state when to choose this over dns_lookup or other sibling tools. There is no exclusion or alternative guidance. The purpose is clear but the 'when-to-use' guidance is only implicit.
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. The verb 'look up' indicates a read-only operation, and the default DNS server is disclosed, but there is no explicit statement that this is safe/non-mutating, nor what happens if no DKIM record exists (e.g., return type, errors). The behavior is simple but not fully transparent.
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, front-loaded sentence followed by a concise parameter list. No wasted words; every line provides useful 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?
The tool is simple and the description covers the essential inputs and examples. An output schema exists, so return values are not required in the description. However, it lacks explicit sibling differentiation and edge-case behavior (e.g., record not found), which would make it more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description fully compensates by clearly explaining each parameter with examples: domain ('example.com'), selector ('selector1', 'google', etc.), and dns_server (default '8.8.8.8'). This adds real meaning beyond the bare schema.
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 states a specific action ('Look up a DKIM record') with a clear resource (DKIM record) and scoping (domain + selector). It naturally distinguishes from siblings like spf_check and dmarc_check because it targets DKIM specifically.
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 usage context is implied by the purpose and examples (e.g., selectors like 'google', 'default'), but there is no explicit guidance on when to choose this tool over alternatives or when not to use it. For example, it does not mention that SPF or DMARC checks would be handled by sibling tools.
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 must carry the full burden of disclosing behavior. It only says 'Look up and parse' and parameter details, but does not explicitly state that it is a safe read-only operation, describe error behavior (e.g., what happens if no DMARC record exists), or mention any side effects or limitations.
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 action line plus two bullet points, with no unnecessary words. It is front-loaded and directly to the point.
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?
The tool is simple, an output schema exists, and the description covers both parameters and the action. However, the absence of annotations means it would benefit from explicitly stating that it is read-only or how it handles missing records. Overall, it is sufficient for basic use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the description compensates by documenting both parameters: 'domain' with an example and 'dns_server' with a default value. This adds clear meaning beyond the bare schema.
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 specifies the action 'Look up and parse' the 'DMARC record for a domain', which is specific and distinct from sibling tools like spf_check, mx_check, or dkim_check that handle other record types.
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 phrase 'Look up and parse the DMARC record' clearly implies when to use this tool (for DMARC checks), but it does not explicitly name alternatives or state when not to use it. It provides clear context without 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, so the description carries the full burden. Yet it only lists parameters and gives no information about return format, error behavior, timeouts, or any caveats. For a network tool, this is a significant gap.
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 sentence plus a clear bullet list of parameters. Every sentence earns its place; no filler or repetition of schema fields.
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?
The tool is simple and output schema exists, so return value explanation is unnecessary. The description covers the operation and parameters well. It loses a point for not referencing specialized siblings or potential limitations, but overall it is sufficient for the task.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description fully compensates by explaining each parameter: domain with an example, record_type with the complete list of accepted values, and dns_server with default and concrete examples. This adds meaning far beyond the bare schema.
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 uses specific verb+resource: 'Look up any DNS record type for a given domain.' It clearly distinguishes from specialized siblings like mx_check or spf_check by emphasizing 'any' record type.
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 context is clear: this is the general-purpose DNS lookup tool. However, it does not explicitly mention when to use this tool versus specialized siblings, nor does it state any exclusions. Lacks explicit alternative naming.
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 the burden of behavioral disclosure. It reveals that the tool checks syntax, counts DNS lookups, warns about the 10-lookup limit, and identifies common errors. This adds significant context beyond the schema and is more than a generic read-only hint.
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 two clear sentences followed by a compact parameter list. Every sentence adds value, with no filler or redundant information. The structure is front-loaded with purpose and behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 params, 1 required), the description covers purpose, behavior, and parameters sufficiently. An output schema exists, so return format doesn't need to be in the description. The warning behavior regarding DNS lookups is an important detail that makes it complete for practical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the description provides meaningful semantics for both parameters: domain with an example and dns_server with its default. This fully compensates for the schema's sparse property 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 'Retrieve and validate the SPF record for a domain' with specific verb and resource, and lists specific validation behaviors (syntax, DNS lookup counting, common errors). This distinguishes it from sibling DNS tools like dns_lookup or mx_check.
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 SPF validation but does not explicitly mention when to use it over alternative tools or exclude other cases. No alternatives are named. The clear scope gives some guidance, but not explicit when/when-not.
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 the burden. It discloses the exact checks performed and the default DNS server behavior. It does not mention potential side effects, rate limits, or output specifics, but the operation is inherently read-only and straightforward, and the output schema exists to handle return values.
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 compact: two sentences and a bulleted parameter list. It front-loads the primary purpose and organizes parameter details cleanly, with no redundant or filler content.
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?
The tool is moderately complex but has only two parameters and an output schema. The description covers the scope and default behavior. It might benefit from stating what the 'overall health assessment' entails, but that is partially addressed by listing the checks, so it is mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description compensates fully. It explains both parameters: 'domain' with an example format and 'dns_server' with its default value. This goes beyond the bare schema and provides the necessary semantic meaning.
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 a specific verb ('Run a comprehensive check') on a resource ('domain's email-related DNS configuration'), and explicitly lists what is checked (A, AAAA, NS, MX, SPF, DMARC). This distinguishes it from sibling tools like spf_check or mx_check which perform individual checks.
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 term 'comprehensive check' implies this is the umbrella tool versus the individual sibling tools. However, it does not explicitly state when to prefer this over the individual checks or provide exclusions, though the context of siblings and the broad scope make the intended usage clear enough.
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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