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ams360-mcp-server

by Scottpedia0

Server Quality Checklist

58%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool targets a distinct resource or action: search_clients for finding clients, get_client for a full record, get_policies for policy data, get_renewals for explaining a limitation, and get_activities for activity-adjacent entities. There is no meaningful overlap.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern: search_clients, get_client, get_policies, get_renewals, get_activities. The pattern is predictable and uniform.

    Tool Count5/5

    The server has 5 tools, which is well within the 3-15 range for a well-scoped integration. Each tool covers a specific aspect of the AMS360 domain without unnecessary bloat.

    Completeness3/5

    The tool set covers core read operations for clients, policies, and activities, but get_renewals is an explanatory tool about an API limitation rather than an actual data-retrieval operation. Write/update capabilities are absent, though this may reflect the underlying API's read-only nature.

  • Average 3.2/5 across 5 of 5 tools scored. Lowest: 1.1/5.

    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
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

  • Behavior1/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are provided, so the description carries the full burden. It discloses no behavioral traits such as whether the tool retrieves data, its side effects, or limitations. The mention of a 'limitation' is vague and does not describe the tool's behavior.

    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 not concise in a useful way—it is under-specified and fails to communicate the tool's purpose. It is not front-loaded with the core action; instead, it presents a confusing statement.

    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 simple two-parameter tool with no output schema or annotations, the description should explain basic usage or return values. It provides none of this, leaving the agent completely uninformed about how to invoke or interpret the tool.

    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?

    The schema defines startDate and endDate as plain strings with no descriptions. The tool description does not mention these parameters or clarify their format, meaning, or relationship. With 0% schema description coverage, the description fails to compensate.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose1/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description does not state what the tool does. It reads as an instruction to 'Explain the current public WSAPI limitation' rather than describing a get_renewals operation. This is misleading and fails to identify the tool's purpose.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines1/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    There is no guidance on when to use this tool versus sibling tools like search_clients or get_policies. The description does not mention any context, 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?

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the scope of entities returned but does not reveal behavior such as required authentication, default filtering behavior, pagination, or return format. 'Retrieve' implies a read operation, but this is not explicit.

    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 that immediately states the verb and resource, followed by a precise list of entities. No wasteful words or redundancy.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool has a nested filter object with many properties, no output schema, and no annotations, the description is too sparse. It does not clarify required filter fields, the meaning of each sub-parameter, or the shape of the response, leaving significant gaps 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.

    Parameters2/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0%, and the description does not explain the 'filter' object or any of its nested properties. It merely lists entity type names that map indirectly to the source enum, but it does not clarify how to use dates, IDs, or boolean flags in the filter.

    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 ('Retrieve') and names a precise resource: the documented AMS360 activity-adjacent entities available in WSAPI v3. It further enumerates the entity types (customer suspenses, common suspenses, personal notes), which clearly distinguishes it from sibling tools like get_client and get_policies.

    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 when to use the tool by focusing on activity-adjacent entities, but it does not explicitly state when to choose this over siblings, nor does it mention any exclusions or alternatives. There is no explicit when-to-use guidance beyond the implied domain.

    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 disclose behavioral traits. It lists searchable fields but omits critical details such as whether matching is exact or partial, the return format, pagination, or behavior with no results. This is a significant gap for a search 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 a single, front-loaded sentence with no redundant phrases. It efficiently conveys the tool's purpose and search parameters.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Despite the simple schema, the description lacks essential context such as return format, result limits, or guidance on how to handle multiple matches. With no output schema and no annotations, the description is not enough for an agent to confidently invoke the tool and interpret results.

    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 only defines 'query' as a string with no description (0% schema coverage). The description compensates by specifying that the query can be a name prefix, customer number, GUID, or policy number, adding valuable meaning to the parameter.

    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 searches AMS360 clients, with specific search criteria (name prefix, customer number, GUID, or policy number). This distinguishes it from sibling tools like get_client, which retrieves a specific client, and get_policies, which handles policies.

    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 finding clients by various identifiers but does not explicitly contrast with alternatives or state when not to use it. Since sibling tools like get_client exist, some usage context is provided, but no direct guidance is given.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are provided, so the description carries the full burden. It states the action ('Fetch') which implies a read operation, and 'full record' suggests complete data. However, it does not disclose potential errors, authentication needs, or what 'full' includes, beyond the basic operation.

    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 uses no unnecessary words. It is front-loaded with the action and resource, followed by the lookup keys, making it easy to parse.

    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 get-by-identifier tool with one parameter and no output schema, the description is largely complete. It conveys the essential function and the key input. It could mention using search_clients when an identifier is not known, but this is a minor gap given the tool's simplicity.

    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?

    Schema coverage is 0%, and the description clarifies that the sole parameter (clientId) accepts either a customer GUID or a customer number. This adds meaningful semantic information not present in the schema, though it could be more explicit about formatting or type expectations.

    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 ('Fetch') and clearly identifies the resource ('full AMS360 customer record') and the lookup keys ('customer GUID or customer number'). It distinguishes this from sibling tools like search_clients and get_policies by focusing on direct retrieval by identifier.

    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 when you have a customer GUID or number, but it does not explicitly state when to prefer this over search_clients or other alternatives. There is no exclusion or alternative mentioned, so it relies on inference from the parameter and tool name.

    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 carries the burden of behavioral disclosure. It indicates a fetch/read operation and mentions return types, but does not detail permissions, errors, or rate limits. This is a moderate disclosure but not a major 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, front-loaded sentence that states the action, resource, and accepted identifier types with no wasted words.

    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 read tool, the description adequately covers the core function and output shape (summaries and hydrated details). While there is no output schema or explicit mention of pagination, the description is sufficient for a straightforward fetch operation.

    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 only defines clientId as a required string with minLength. The description adds meaningful semantics by explaining that clientId can be a customer GUID or customer number, which the schema alone does not convey. It does not specify exact format or validation, so not a 5.

    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 ('Fetch') and resource ('policies') with qualifiers ('for an AMS360 customer GUID or customer number'), clearly stating what the tool does. This distinguishes it from sibling tools like search_clients and get_client, 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 description provides clear context: use this tool when you need policy summaries or hydrated details for a specific customer by GUID or number. It does not explicitly name alternatives or when-not conditions, but the scope 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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