cybersec-mcp

by fa1829

Overview Schema Related Servers Score Discussions

Python

Remote

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool maps to a distinct security task: hash analysis, CVE lookup, header scanning, WHOIS recon, payload decoding, password strength, and report generation. Even analyze-hash and decode-payload are clearly separated by their descriptions and use cases.
Naming Consistency4/5
Names are consistently lowercase with hyphens, and most follow a clear verb-noun pattern such as analyze-hash, check-cve, and scan-headers. Minor deviations like whois-lookup and password-strength are still readable but break the strict verb-first convention.
Tool Count5/5
With 7 tools, the server is well-scoped and each tool provides a meaningful, non-redundant capability. The count is appropriate for a cybersecurity-focused MCP server without feeling bloated or thin.
Completeness4/5
The set covers common security workflows including reconnaissance, CVE research, hash analysis, payload decoding, password policy checks, and threat report generation. Minor gaps exist such as IP reputation enrichment or URL scanning beyond headers, but the core surface is solid.
Average 4/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit 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
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?
No annotations are provided, so the description must carry the behavioral burden. It states supported encodings but does not disclose what the 'auto' mode returns (single result, list, order, or failure behavior), how errors surface, or any limitations. For a tool that can attempt multiple decodings, this is a meaningful 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?
A single sentence that front-loads the core purpose and immediately follows with supported encodings. Every phrase earns its place; there is no fluff or redundancy beyond useful context.
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?
The tool is simple with two parameters and no output schema, but the description does not explain how results are returned, especially when 'auto' is used. An agent could call it correctly but may not know how to interpret multiple possible decodings or failures. This leaves an important behavioral gap.
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 context about use cases but no additional parameter-level detail beyond the schema. It does not explain payload format constraints or encoding edge cases, though the schema already documents both parameters adequately.
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 ('Decode') and resource ('obfuscated or encoded payloads'), and gives concrete contexts (malware analysis, CTF, phishing). It clearly distinguishes this tool from all siblings, none of which are decoding tools, so an agent can select it confidently.
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 when to use it: whenever an encoded/obfuscated payload is encountered in relevant security contexts. It does not explicitly name alternatives or exclusions, but sibling tools are sufficiently unrelated that no negative guidance is necessary. A clear context is 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, the description carries the burden of explaining behavior. It discloses the external source (NIST NVD) and the data returned, which is useful. However, it does not mention potential rate limits, network dependency, error behavior, or that this is a read-only lookup.
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?
A single, focused sentence that front-loads the action and source before listing expected output fields. Every word contributes meaning and there is 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?
For a one-parameter lookup tool with no output schema, the description provides a clear picture of what the agent will get back and where the data comes from. Minor gaps like error handling and external service unpredictability prevent a perfect score.
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% and the parameter already includes a clear example ('CVE-2021-44228 (Log4Shell)'). The tool description adds no additional parameter-level meaning, so the baseline score of 3 applies.
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'), names the resource ('CVE ID from NIST NVD'), and lists concrete return fields. It is clearly distinct from the sibling tools, which address hashes, headers, WHOIS, payloads, and passwords.
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 intended use is implicit: call this when you have a CVE ID and want vulnerability details. However, it does not explicitly state when to prefer this tool over alternatives or when not to use it. The schema's example hints at usage, but no direct guidance exists.
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 disclosure burden. It truthfully reveals the optional VirusTotal query, which is a meaningful external network behavior. However, it does not clarify how the 'optional' is triggered given that the schema only contains one required hash parameter, nor does it explain behavior for unrecognized hashes or whether both outputs are always returned.
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, dense sentence that front-loads the core purpose and appends the optional secondary behavior with no redundant words.
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?
The tool itself is simple and the one parameter is fully documented, but the ambiguous 'optionally query VirusTotal' behavior is not explained. With no output schema and no option param in the schema, an agent cannot tell exactly when the VirusTotal query occurs or what the return shape will be, making the descition incomplete for fully informed invocation.
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% and the single 'hash' parameter is already well documented in the input schema. The description adds minimal new meaning beyond the schema, only mentioning example hash types, so the baseline 3 applies.
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 verbs 'identify' and 'query' with concrete resources: hash algorithm type and VirusTotal reputation/threat intelligence. It clearly distinguishes this tool from siblings like check-cve, whois-lookup, and scan-headers, which address different domains.
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 a clear use case: analyzing a hash to determine its algorithm and optionally enriching it with VirusTotal data. However, it does not explicitly state when not to use this tool or name alternative tools for similar tasks, so it falls just short of a 5.
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, the description carries the transparency burden. It discloses the tool's main behavior: generating a formatted report with risk rating, IOCs, and recommendations. It does not mention side effects, permissions, persistence, or whether it enriches data externally, but for a report-generation tool the core behavior is adequately described.
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?
Two focused sentences with no filler. The first sentence states the core purpose and the second efficiently lists supported inputs and expected outputs. The most relevant information is front-loaded.
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 9-parameter tool with no output schema, the description provides a solid mental model of inputs and outputs. It could be stronger by mentioning the required target and by distinguishing itself from the sibling tools, but the overall picture is sufficient for an agent to invoke 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?
Schema coverage is 100%, so the baseline is 3. The description adds value by explaining that inputs can be provided in any combination and that observations are free-form, but it omits the required 'target' parameter from its summary and does not elaborate on severity, attack_type, or threat_actor semantics beyond the 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 the specific verb 'Generate' with a clear resource ('structured threat intelligence report') and names the input types (domain, IP, hash, CVE IDs, observations) and output components (risk rating, IOCs, recommended actions). This clearly distinguishes it from the sibling analysis/lookup tools.
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 clearly establishes the usage context: gather findings and produce a consolidated TI report. It implies this is the right tool after collecting data, and it is implicitly distinct from the single-purpose siblings. However, it does not explicitly state when not to use it or name an alternative.
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, the description carries the full burden of disclosing side effects. It clearly states the main behavior—fetching and auditing headers—which implies a read-only network operation. However, it does not mention potential error cases, timeout behavior, or requirements like the URL being reachabe, which would be valuable for a network-reaching tool.
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?
A single, well-structured sentence that front-loads the action and resoruce, followed by a concise list of audited headers. Every phrase contributes meaning without redundancy.
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 tool with one required parameter and no output schema, the description provides the necessary context for correct invocation: it names the resource, the action, and the evaluation criteria. It does not describe the exact return format, but for such a simple tool that is a minor gap, and the absence of an output schema lowers the burden.
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 covers the sole parameter (url) with a descriprion and format, so the 100% coverage gives a baseline of 3. The tool description adds context about what will be done with the URL (fetch and audit) but does not addfurther parameter-level detail beyond what the schema already provides.
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 descripion states a specific verb ('fetch') and resource ('HTTP response headers from a URL'), and explicitly enumerates the security headers it audis (CSP, HSTS, X-Frame-Options), making its purose unmistakabe. The tool clearly differs from siblings ike check-cve or whois-lookup, which target different resources.
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 descripion conveys a clear use case: audit a URL's HTTP response headers for security best practices. Although it does not explicitly name alternatives or exclusion conditions, the context is sufficient for an agent to recognize when this tool is appropriate, and no sibling could plausibly compete with this functionality.
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?
No annotations are provided, so the description carries the full burden. It explicitly discloses the critical privacy behavior: 'Does NOT store or transmit the password' and 'processed locally' appears in the schema. It also enumerates the evaluation dimensions, giving a clear operational picture. It does not describe the return format, but that is a minor gap for a read-only analysis tool.
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 with no wasted words. It front-loads the primary purpose, then provides the specific checks and the crucial privacy guarantee. Every sentence earns its place.
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 one-parameter tool, the description covers the standard, the checks performed, and the privacy behavior. The main gap is that no return value or output shape is described, which is more noticeable because there is no output schema. Still, the overall context is adequate for an agent to select and invoke the tool 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?
Schema coverage is 100%, so the only parameter 'password' is already fully documented with a description that includes local processing and no storage or transmission. The tool description reinforces the purpose but adds little parameter-specific meaning beyond the schema, so the baseline score of 3 is appropriate.
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 names a specific verb ('Analyze'), a clear resource ('password strength'), and a concrete standard ('NIST SP 800-63b guidelines'), then lists the exact checks performed. This distinguishes it from all sibling tools, which target unrelated security tasks like hash analysis, CVE checks, and header scanning.
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 makes the tool's context obvious: it is for evaluating password strength using NIST guidelines, with explicit scope of checks. It does not name alternatives or state when not to use it, but the sibling tools are sufficiently different that an agent can safely infer when this tool applies.
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?
No annotations are provided, so the description carries the behavioral burden. It states the operation is 'passive' reconnaissance via 'public APIs', which conveys a read-only, non-intrusive behavior. It lists the returned information categories, giving the agent a clear expectation of the outcome.
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 short sentences with no filler. The core action and target are front-loaded, and the return summary is specific without being bloated.
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 has a single required parameter, no output schema, and no dependencies or prerequisites mentioned. The description enumerates the expected return items, which is sufficient for an agent to decide to call it, though it could note error cases or rate-limit 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?
The schema includes 100% parameter documentation with a clear example ('example.com'). The description adds little beyond restating that a domain is the target, but the schema already fully covers the single parameter's semantics.
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 ('Perform') and resource ('WHOIS and passive DNS reconnaissance on a domain'), then lists the concrete output types returned. This clearly differentiates it from the sibling tools, which target hashes, CVEs, headers, payloads, passwords, and reports.
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?
It clearly implies this tool is for domain-focused recon and passively gathering registration/DNS data. It does not explicitly state when not to use it, but none of the sibling tools overlap with domain reconnaissance, so the intended use is unambiguous.
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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