JSM Assets MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
The tools are mostly distinct, with clear separation between metadata retrieval (get_object_attributes, get_object_schemas, get_object_types) and search operations (search_assets_aql, search_child_objects). However, the two search tools could potentially be confused, as both handle search with filters and pagination, though they target different scopes (general AQL vs. child-specific).
Naming Consistency5/5
All tool names follow a consistent snake_case pattern with clear verb_noun structure (e.g., get_object_attributes, search_assets_aql). The naming is predictable and readable throughout the set, with no deviations in style or convention.
Tool Count4/5
With 5 tools, the count is reasonable for a JSM Assets server, covering core metadata and search operations. It is slightly lean but well-scoped, as each tool serves a distinct purpose without obvious bloat or redundancy, though it might benefit from additional CRUD tools for completeness.
Completeness3/5
The toolset provides good read/search capabilities for JSM Assets, including metadata exploration and asset queries. However, there are notable gaps in CRUD operations—no tools for creating, updating, or deleting assets or schemas, which limits agents to read-only workflows and may cause failures in scenarios requiring modifications.
Average 3.2/5 across 5 of 5 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?
With no annotations provided, the description carries full burden but lacks behavioral details. It states this is a read operation ('Get'), but doesn't disclose permissions needed, rate limits, pagination, error conditions, or what the return format looks like. It adds minimal context beyond the basic purpose.
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 concise sentences with zero waste. It is front-loaded with the core purpose and efficiently explains what attributes are, earning its place without unnecessary elaboration.
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 no annotations and no output schema, the description is incomplete for a tool that retrieves data. It doesn't explain what the return values look like (e.g., list of attributes with details), error handling, or behavioral constraints, leaving significant gaps for an agent to use it effectively.
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 schema already documents the single parameter 'objectTypeId'. The description adds no additional meaning about the parameter, such as where to find object type IDs or format examples. Baseline 3 is appropriate when schema does the heavy lifting.
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 verb ('Get') and resource ('attributes for a specific object type'), specifying what data is retrieved. It distinguishes from sibling tools like 'get_object_types' by focusing on attributes rather than types or schemas, though it doesn't explicitly name alternatives.
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?
The description provides no guidance on when to use this tool versus alternatives like 'get_object_schemas' or 'get_object_types'. It mentions attributes define data storage, but offers no explicit context, exclusions, or prerequisites for usage.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Get all object types') but lacks details on permissions required, rate limits, pagination, or what 'all' entails (e.g., if there are limits on the number returned). The second sentence explains what object types are, but this is conceptual rather than behavioral. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it operates.
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 appropriately sized with two sentences: the first states the purpose, and the second provides conceptual context about object types. It is front-loaded with the core action. However, the second sentence, while informative, could be considered slightly extraneous if the agent already understands object types from other sources, but it doesn't significantly detract from 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 low complexity (1 parameter, no output schema, no annotations), the description is minimally adequate. It explains what the tool does but lacks details on behavioral aspects like permissions or output format. Without an output schema, the description doesn't clarify what is returned (e.g., a list of type names or full definitions), which is a gap. It meets basic needs but leaves room for improvement in context.
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 input schema has 100% description coverage, with 'schemaId' clearly documented as 'The ID of the object schema to get types for'. The description adds no additional parameter information beyond what the schema provides, such as format examples or constraints. Since schema coverage is high (>80%), the baseline score of 3 is appropriate, as the schema does the heavy lifting without extra value from the description.
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 verb ('Get') and resource ('all object types for a specific schema'), making the purpose understandable. It distinguishes from siblings like 'get_object_attributes' or 'get_object_schemas' by focusing on types rather than attributes or schemas themselves. However, it doesn't explicitly differentiate from 'search_assets_aql' or 'search_child_objects', which might also involve object types indirectly.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a schema ID), exclusions, or comparisons to siblings like 'get_object_schemas' (which might list schemas before selecting one for types). Usage is implied through the parameter 'schemaId', but no explicit context 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that 'Schemas contain related object types', adding some context about the data structure, but fails to address critical aspects like whether this is a read-only operation, potential rate limits, authentication needs, or what the output format looks like (e.g., list of schema names vs. full details). This leaves significant gaps for a tool with zero annotation coverage.
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, efficient sentence that front-loads the core action ('List all object schemas') and adds necessary context ('available in the JSM Assets workspace') without any wasted words. Every part earns its place, making it highly concise and well-structured.
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 (0 parameters, no output schema, no annotations), the description is adequate but has clear gaps. It explains what the tool does but lacks usage guidelines, behavioral details (e.g., read-only nature, output format), and differentiation from siblings. For a basic list tool, this is minimally viable but not fully complete.
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 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately avoids redundant parameter details, and the baseline score for zero parameters is 4, as it doesn't need to compensate for any gaps in schema coverage.
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 verb ('List') and resource ('all object schemas') with context ('available in the JSM Assets workspace'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_object_types' or 'get_object_attributes', which might have overlapping scopes, preventing a perfect score.
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?
The description provides no guidance on when to use this tool versus alternatives such as 'get_object_types' or 'search_assets_aql'. It lacks explicit instructions on use cases, prerequisites, or exclusions, leaving the agent with minimal context for tool selection.
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 of behavioral disclosure. It adds some context: 'Supports complex queries with filters' and 'robust automatic pagination,' which hints at capabilities beyond basic search. However, it does not cover critical aspects like authentication needs, rate limits, error handling, or what 'robust' pagination entails, leaving gaps in transparency 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 concise and front-loaded: it states the core purpose in the first sentence and adds key features in the second. Every sentence earns its place by providing essential information without waste, making it efficient and well-structured.
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 complexity (6 parameters, no output schema, no annotations), the description is somewhat complete but has gaps. It covers the purpose and hints at capabilities but lacks details on return values, error cases, or integration with sibling tools. Without an output schema, the description should ideally explain what results look like, but it doesn't, making it adequate but not fully comprehensive.
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 input schema has 100% description coverage, so the schema already documents all parameters thoroughly. The description does not add any meaning beyond the schema (e.g., it doesn't explain AQL syntax or pagination behavior further). According to the rules, with high schema coverage, the baseline is 3, which is appropriate here as the description doesn't compensate but doesn't detract either.
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's purpose: 'Search JSM Assets using AQL (Assets Query Language).' It specifies the verb ('Search'), resource ('JSM Assets'), and method ('using AQL'), which is specific and informative. However, it does not explicitly distinguish this tool from its siblings (e.g., 'search_child_objects'), missing full differentiation for a score of 5.
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 by mentioning 'Supports complex queries with filters and robust automatic pagination,' suggesting it's for advanced searches. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., 'search_child_objects') or any exclusions, leaving usage context implied rather than clearly defined.
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 of behavioral disclosure. It mentions 'robust automatic pagination,' which adds valuable context about how results are fetched. However, it doesn't disclose other important behavioral traits such as whether this is a read-only operation, potential rate limits, authentication requirements, error conditions, or what the return format looks like. The description adds some behavioral context but leaves significant gaps.
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, well-structured sentence that efficiently communicates the core functionality: searching child objects, optional filters, and automatic pagination. Every element earns its place with zero wasted words, making it appropriately sized and front-loaded for quick understanding.
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 complexity (5 parameters with nested objects, no output schema, and no annotations), the description is moderately complete. It covers the main purpose and hints at behavior (pagination), but lacks details on return values, error handling, or how this tool relates to siblings. Without annotations or output schema, the description should ideally provide more context about what results look like and operational constraints.
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 schema already documents all parameters thoroughly. The description mentions 'optional filters' and 'robust automatic pagination,' which aligns with the schema but doesn't add significant semantic meaning beyond what's already in the parameter descriptions. No additional parameter context or examples are provided in the description, so it meets the baseline for high schema coverage.
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's purpose: 'Search for child objects of a specific parent object type' - this is a specific verb+resource combination. However, it doesn't explicitly distinguish this tool from sibling tools like 'search_assets_aql' or 'get_object_types', which might also involve searching or retrieving object information. The description is clear but lacks sibling differentiation.
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 context through 'with optional filters and robust automatic pagination,' suggesting this is for retrieving child objects with filtering capabilities. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'search_assets_aql' or 'get_object_types,' nor does it mention any prerequisites or exclusions. The usage is implied rather than explicitly stated.
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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