MEOK MCP Hardening MCP
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool targets a distinct security audit task: full server audit, per-description scan, specific vulnerability checks, template generation, listing rules, and signing reports. No overlap in purpose.
Naming Consistency3/5Tool names use underscore and follow verb_noun pattern, but verbs vary: 'audit', 'check', 'generate', 'list', 'sign'. While readable, the mix of verbs reduces consistency compared to a uniform pattern.
Tool Count5/57 tools is well-scoped for a security hardening server. Each tool addresses a distinct need without being too few or excessive.
Completeness4/5Covers core audit workflows: full server audit, per-tool scan, specific checks (destructive, supply chain), template generation, reference map, and report signing. Minor gap: no direct apply/patch tool, but overall comprehensive.
Average 3/5 across 7 of 7 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 17 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
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It mentions scanning for signals but doesn't explain effects, return values, or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, concise and front-loaded, but sacrifices completeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complex object parameter, no output schema, and no annotations, the description is severely incomplete for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'tool' is an object with no description in schema or explanation in the tool description. 0% schema coverage means the description adds no meaning.
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 purpose: deep-scan a single tool description for specific signals (injection, destructive, spoof). However, it does not differentiate from sibling tools like 'audit_server_json' or 'check_destructive_surface'.
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 on when to use this tool versus alternatives, or any prerequisites or 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?
No annotations are provided, so the description must carry the full burden. It mentions HMAC-sealing but does not explain side effects, return format, or whether the input is modified. The behavioral disclosure is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (one sentence) but at the cost of completeness. It front-loads the action but omits necessary details, making it efficient but underinformative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, annotations, and parameter documentation, the description is far from complete. It does not explain return values, behavior, or constraints, leaving critical gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'audit_result' is an object with no schema description (0% coverage). The description adds no information about its structure or required fields, leaving the agent without guidance on what to pass.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (HMAC-seal) and the resource (audit result) and the purpose (publish as signed badge). It is specific and distinguishes from sibling tools that focus on auditing or checking.
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, no prerequisites, and no conditions for use. It only states what it does, not why or when.
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 provided, so the description must cover behavioral traits. It states 'audit' (suggesting read-only) but does not confirm idempotency, auth requirements, or potential side effects. No details on return format or pagination.
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?
Single sentence, no wasted words. However, extreme brevity borders on under-specification, but conciseness itself is good.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool performing a complex security audit with one richly structured input and no output schema, the description is woefully incomplete. It does not explain what the input should contain, what the output includes, or any actionable details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage (no parameter descriptions). The tool description adds no meaning beyond repeating the parameter name 'server_json'. The agent has no clue about required structure or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific scope: 'Full OWASP LLM Top 10 + MCP-specific security audit of an MCP server.json.' It distinguishes from siblings like audit_tool_description by specifying the audit framework and context.
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 on when to use this tool versus alternatives like check_destructive_surface or list_owasp_findings. The agent is left to infer from the name alone.
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 behavioral disclosure. It states it 'return only supply-chain findings', indicating a filtering behavior, but does not describe what 'pin + provenance audit' entails or any side effects. It adds some context but remains vague.
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, front-loaded sentence that efficiently states the purpose. It is appropriately sized with no wasted words, though it could be slightly more detailed.
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 lack of output schema and the nested object parameter, the description is incomplete. It fails to explain the parameter or the meaning of 'pin + provenance audit', leaving gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter 'server_json' with no description (0% coverage). The tool description does not explain the parameter at all, providing no added meaning beyond the schema name.
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 verb 'return' and the resource 'supply-chain findings (LLM05)', and mentions 'pin + provenance audit' for specificity. It differentiates from sibling tools like 'list_owasp_findings' by focusing on a specific category.
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 on when to use this tool versus siblings or when not to use it. The description does not mention alternatives or 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 exist, so the description must disclose behavioral traits. It says 'fast gate' implying lightweight but does not explain side effects, state changes, or behavior on invalid input. Lack of detail on whether it modifies data or is read-only.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is a single sentence, concise but overly brief. It could add essential parameter and usage details without becoming verbose.
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 no output schema, one undocumented nested object parameter, and low schema coverage, the description is insufficient. It fails to specify server_json format, return structure, or error conditions, making the tool hard to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has one required object parameter 'server_json' with 0% description coverage. The description provides no guidance on the parameter's structure, purpose, or expected content, leaving the agent without crucial context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'destructive-surface findings (LLM08)' and is a 'fast gate for CI'. It specifies the exact subset (LLM08) and distinguishes from siblings like 'list_owasp_findings' or 'check_supply_chain' by limiting scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions 'fast gate for CI' providing usage context, but does not explicitly state when not to use it or suggest alternatives. No exclusion criteria or comparison to sibling tools is given.
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 full burden. It discloses that the tool generates a starter template but does not explain what 'scores A' means, whether it is destructive, requires permissions, or has side effects. Minimal behavioral context.
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, front-loaded sentence of 9 words. Every word is meaningful with no redundancy. It is appropriately sized for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and no output schema, the description provides a clear purpose. However, it assumes the agent understands 'scores A' without further explanation. For a minimal tool, this is nearly complete.
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 tool has zero parameters and the schema coverage is 100% (empty). The description adds no parameter details, but with no parameters, the baseline is 4. It does not explain why there are no options, but that is not a major gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a server.json starter that 'scores A', indicating a specific quality. The verb 'generate' and resource 'template' are present, and it is easily distinguishable from sibling tools like audit_server_json and sign_security_report.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a minimal-passing template is needed, but provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. Siblings suggest audit and checking contexts, but this is not stated.
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 must disclose behavior. It states the return value, but does not explicitly confirm it is read-only, idempotent, or safe to call frequently. The absence of side effects is implied but not stated.
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 sentence that is front-loaded and to the point. Every word is necessary and adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters, no output schema, and is a straightforward list retrieval, the description is sufficient. However, more detail about the output format (e.g., key-value structure) could enhance completeness.
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 tool has no parameters, so the description does not need to add meaning beyond the schema. The baseline for zero parameters is 4, and the description does not contradict or miss any parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns the canonical OWASP LLM Top 10 (2025) to MCP-Hardening rule map, using a specific verb and resource. It distinguishes from sibling tools like audit_server_json and check_destructive_surface, which focus on auditing and checking.
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 on when to use this tool versus alternatives. The description lacks any context about typical use cases or prerequisites, though the tool's simplicity partially mitigates this.
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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