APAC Compliance MCP

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool targets a distinct aspect of APAC business: compliance checks, country briefs, etiquette, follow-up cadence, full context pack, outreach templates, and stakeholder navigation. No overlapping purposes.
Naming Consistency5/5
All tools follow a consistent 'get_<descriptive_noun>' pattern (e.g., get_compliance_check, get_stakeholder_map). No deviation in style or verb usage.
Tool Count5/5
Seven tools is well-scoped for a regional compliance MCP. Each tool serves a clear function without redundancy or deficiency.
Completeness5/5
The tool set covers compliance, cultural context, etiquette, follow-up strategies, outreach templates, stakeholder mapping, and a comprehensive pack. No obvious gaps for the intended domain.
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
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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 present, and the description does not disclose behavioral traits such as whether the tool is read-only, the size of the response, or any side effects. The phrase 'for fine-tuning or full agent context' hints at a large output but 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.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, but it is too brief for a tool with no parameters and no output schema. It lacks detail on what the APAC pack contains, making it under-specified rather than concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no input schema, no output schema, and no annotations, the description must fully explain the return value. It fails to describe the contents or structure of the 'APAC pack,' leaving the agent without adequate information to use the tool effectively.
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 tool has zero parameters, and the schema coverage is 100%. The description does not need to add parameter meaning, so this dimension scores high. However, it could have clarified that no input is required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies the tool returns an 'APAC pack' for fine-tuning or full agent context, which indicates a comprehensive data bundle. However, it lacks detail on the pack's contents, making it less specific than sibling tools like get_compliance_check or get_country_brief, which have clearer purposes.
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?
No explicit guidance is provided on when to use this tool versus alternatives. The description does not differentiate use cases, such as when a full pack is preferred over individual packs like get_outreach_template.
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 description must carry full burden. It mentions APAC-specific notes but does not disclose output format, side effects, or any constraints (e.g., data freshness, permissions). Minimal behavioral context beyond function.
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?
Two sentences, no fluff, front-loaded purpose. Could be more structured (e.g., separate parameter description) but remains efficient for a simple tool.
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 output schema and only one enum parameter, the description provides enough to understand the tool's purpose. However, lacking details on what the map contains, how it's structured, and support for other stages beyond the APAC note leaves gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and description only says 'by company stage' without explaining the enum values or their meanings. The parameter is not explicitly described, so the description adds little 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?
Clearly states it provides a stakeholder navigation map filtered by company stage, with APAC-specific notes. Distinguishes from siblings which cover compliance, country briefs, etc. However, 'navigation map' is somewhat vague but sufficient.
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?
No explicit guidance on when to use this tool versus alternatives like get_full_apac_pack or get_etiquette_guide. Only implies APAC context via the second sentence, but does not state prerequisites 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?
Without annotations, the description carries full burden but only hints at content areas. It fails to disclose behavioral traits such as response format (e.g., text, structured data), length, or any limitations. An agent cannot predict what the output will look like.
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 concise: a single sentence listing key topics. It effectively front-loads the purpose. However, it could benefit from a clearer structure, such as specifying that the parameter selects the country, and perhaps a brief note on output format.
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 simple nature of the tool (single enum parameter), the description covers the core purpose adequately. However, it lacks completeness in specifying what the user receives (e.g., a textual guide, list of norms) and does not mention any output schema or return type, which limits the agent's ability to handle the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema description coverage at 0%, the description must compensate for the parameter 'country'. It does not mention the parameter at all, nor the available enum values (e.g., japan, singapore). The description adds no meaning beyond the schema itself.
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 that the tool provides business etiquette per country, listing specific topics like meishi protocol, gift culture, drinking culture, hierarchy norms, and religious awareness. This distinctly differentiates it from sibling tools which focus on compliance, brief overviews, followups, outreach, and stakeholder mapping.
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?
No guidance is provided on when to use this tool versus alternatives like get_country_brief or get_compliance_check. There is no mention of context or prerequisites, leaving the agent to infer usage solely from the tool name.
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 carries full burden. It mentions calibrated templates but does not disclose any behavioral traits like auth needs, mutability, or whether templates are static. For a simple retrieval tool, the description is minimal.
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?
One concise sentence that efficiently conveys the purpose and key differentiator. No unnecessary words, but could benefit from slightly more structure (e.g., listing parameters).
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 low complexity (2 params with enums, no output schema), the description is adequate for basic understanding. It covers what the tool does and the key customization factor. However, it omits return format or how to use the templates, leaving some ambiguity.
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 0%, but description adds meaning by explaining country parameter specifies local norms. Channel is implied as outreach channel. Enums in schema already clarify values, and description adds context about calibration but not explicit parameter definitions.
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 it provides country-specific outreach templates calibrated to local norms. The verb is implied (get/retrieve) and the resource is templates. It distinguishes from sibling tools by focusing on outreach templates rather than briefs, etiquette, or stakeholder maps.
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?
No guidance on when to use this tool instead of siblings like get_etiquette_guide or get_country_brief. The description implies use for outreach templates but does not provide selection criteria or context.
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 describes what data is returned (compliance info), implying a read-only operation. However, it does not explicitly state that it is safe, has no side effects, or requires any authentication. For a simple retrieval tool with one parameter, the description is minimally adequate but lacks explicit safety assurances.
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 concise sentence that covers the tool's purpose without any unnecessary words. It is front-loaded with the key function ('Country-specific compliance') and lists the output components efficiently. This is a model of conciseness.
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 (one parameter, no output schema), the description provides the essential information: it returns compliance data. However, it does not mention the response structure, pagination, or how to interpret the data. For a tool with siblings, missing this context reduces completeness. It is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter ('country') with an enum list but no description. Schema description coverage is 0%, so the description should compensate by explaining the parameter. It does not mention the parameter at all, leaving the agent to infer its meaning from context. The enum values are clear, but the description adds no 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 clearly states the tool provides country-specific compliance data including data protection framework, regulator, risks, and spam law. This distinguishes it from sibling tools like get_etiquette_guide or get_country_brief, which cover different aspects. The verb is implicit from the tool name ('get'), and the resource is clear. A more explicit verb could boost clarity further.
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?
No guidance is provided on when to use this tool versus alternatives like get_country_brief or get_full_apac_pack. The description does not mention use cases, prerequisites, or exclusions. This omission makes it harder for an agent to decide between siblings.
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, and the description does not disclose any behavioral traits (e.g., read-only, rate limits, response format). It only lists the content covered, which is insufficient for a tool that likely performs a query.
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 a single sentence listing all relevant topics without wasted words. However, it could be structured as bullet points for easier parsing.
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 description adequately covers what information the tool returns, but it lacks details on the format (e.g., plain text, JSON) and does not reference the output schema (which is absent). Given the single parameter and sibling context, it is marginally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'country' has an enum list of 8 APAC countries. The description does not add any meaning beyond the schema; it does not explain the parameter's role or provide examples. With 0% schema description coverage, the description should compensate but fails to do so.
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 tool provides country-specific APAC buyer psychology, communication style, sales cycle, compliance, etc. It is distinct from siblings like get_compliance_check and get_etiquette_guide, which focus on narrower aspects.
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 the tool is for a high-level country overview, but it does not explicitly state when to use it versus siblings. No when-not-to-use guidance is provided, leaving the agent to infer from context.
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 present, so the description must convey behavioral traits. It describes the output (e.g., slow vs fast cadence, gap days) but does not explicitly state side effects, idempotency, or authorization needs. The 'get' prefix implies read-only, but it is not confirmed.
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 conveys the core functionality and key examples. No unnecessary words or 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 parameter and no output schema, the description provides a good summary of what to expect. However, it does not cover all eight enumerated countries or specify the exact output format (e.g., string, object), which could be considered incomplete.
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 has 0% description coverage, but the description compensates by providing concrete examples of expected behavior for three countries (Japan, Singapore, India), thereby adding meaning beyond the enum list. It helps the agent understand how different parameter values affect output.
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 tool provides country-specific follow-up cadence, with specific examples of behavior for Japan, Singapore, and India. The verb 'get' and resource 'follow-up cadence' are specific, and the examples distinguish it from sibling tools like get_compliance_check or get_stakeholder_map.
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?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, nor any comparison with sibling tools such as get_outreach_template or get_etiquette_guide, leaving the agent to infer usage context.
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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