Xray MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes focused on different aspects of test management (creation, querying, execution, import), but there is some potential overlap between 'create_test_execution' and 'execute_tests' where the latter might be confused as a superset of the former. The descriptions help clarify that 'execute_tests' specifically creates and runs tests, while 'create_test_execution' is just a container, but the naming could cause mild confusion.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with snake_case (e.g., 'associate_tests_to_execution', 'create_test_execution', 'get_test_info'). There are no deviations in naming conventions, making the set predictable and easy to parse for an agent.
Tool Count5/5
With 8 tools, the server is well-scoped for test management in Xray, covering key operations like creation, querying, execution, and import without being overly complex or sparse. Each tool appears to serve a specific function that contributes to the domain's workflow.
Completeness4/5
The tool set provides strong coverage for test execution and management, including CRUD-like operations (create, query, update) and import capabilities. A minor gap is the lack of tools for deleting or archiving test executions or plans, which might limit full lifecycle management, but agents can likely work around this with existing tools.
Average 2.9/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 2 community issues answered or closed 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 for behavioral disclosure. It states the action is 'Add test cases' which implies a mutation operation, but doesn't address permissions, whether this is idempotent, what happens if test keys already exist in the execution, or any rate limits. The description is minimal and lacks 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's appropriately sized for this tool and front-loads the core purpose immediately.
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?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after adding tests (e.g., execution status changes), what the response looks like, or potential error conditions. Given the complexity of modifying test executions, more context would be helpful.
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 both parameters ('executionKey' and 'testKeys'). The description adds no additional meaning beyond what the schema provides - it doesn't explain format expectations, constraints, or relationships between parameters. 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 action ('Add test cases') and target resource ('to an existing test execution'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'update_test_execution' or 'execute_tests', which might have overlapping functionality.
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 'update_test_execution' or 'execute_tests'. It mentions 'existing test execution' as a prerequisite but doesn't specify exclusions or contextual usage scenarios.
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 'Create a new test execution container', implying a write operation, but doesn't mention permissions, side effects, error handling, or response format. This is inadequate for a mutation 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 directly states the tool's purpose without unnecessary words. It's front-loaded and appropriately sized, making it easy for an agent to parse quickly.
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 complexity of a creation tool with no annotations and no output schema, the description is incomplete. It lacks information on behavioral traits, return values, and usage context, which are critical for an agent to invoke the tool correctly in a real-world scenario.
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%, meaning all parameters are documented in the schema. The description doesn't add any additional meaning beyond what's in the schema, such as explaining relationships between parameters or usage examples. Baseline 3 is appropriate when the schema handles parameter documentation.
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 'Create' and the resource 'new test execution container in Xray', which specifies what the tool does. However, it doesn't differentiate from sibling tools like 'update_test_execution' or 'associate_tests_to_execution', which would require mentioning creation versus modification or association.
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. For example, it doesn't specify if this is for initial setup versus updates, or when to choose this over 'update_test_execution' or 'associate_tests_to_execution'. This lack of context leaves the agent without clear usage instructions.
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. While 'Create and execute' implies a write/mutation operation, the description doesn't address critical aspects like required permissions, whether this is an atomic operation, what happens on failure, rate limits, or what the output looks like (especially since there's no output schema). This leaves significant gaps for a tool that performs creation operations.
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 directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded with the core functionality, making it easy for an agent to parse quickly.
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?
For a tool that creates and executes test runs (a mutation operation) with 5 parameters and no output schema, the description is insufficient. It lacks information about behavioral traits (permissions, side effects), doesn't differentiate from sibling tools, and provides no guidance on usage context. The 100% schema coverage helps with parameters, but overall completeness is poor for this type of operation.
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 all parameters are documented in the schema. The description adds no additional parameter information beyond what's already in the schema descriptions (e.g., it doesn't explain relationships between parameters or provide examples beyond the schema). This meets the baseline expectation when schema coverage is complete.
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 action ('Create and execute a test run') and the resource ('in Xray for specified test cases'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from sibling tools like 'create_test_execution' or 'associate_tests_to_execution', which likely have overlapping functionality in the Xray test management context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. With sibling tools like 'create_test_execution' and 'associate_tests_to_execution' available, there's no indication of the specific scenarios, prerequisites, or differences that would help an agent choose this tool over others in the test execution workflow.
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. While 'Retrieve' implies a read-only operation, it doesn't specify aspects like authentication requirements, rate limits, error handling (e.g., what happens if the test key is invalid), or the format of the returned information. For a tool with zero annotation coverage, this is a significant gap in transparency.
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 purpose ('Retrieve detailed information about a specific test case') with zero wasted words. It's appropriately sized for a simple tool with one parameter and no complex behavioral nuances to explain.
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 lack of annotations and output schema, the description is incomplete for a tool that retrieves 'detailed information'. It doesn't hint at what information is returned (e.g., test status, steps, attachments) or potential side effects. While the schema covers the single parameter well, the overall context for the agent to use this tool effectively is lacking.
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 the 'testKey' parameter clearly documented as a 'Test issue key (e.g., "PROJ-123")'. The description adds no additional parameter details beyond what the schema provides, such as examples of valid keys or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the 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 ('Retrieve') and resource ('detailed information about a specific test case'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_test_plans' or 'query_test_executions', which might also retrieve test-related information but with different scopes or filters.
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 valid test key), exclusions, or comparisons to siblings like 'get_test_plans' (which might retrieve broader test plan info) or 'query_test_executions' (which might filter executions). This leaves the agent to infer usage from context alone.
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 'List test plans' but does not mention any behavioral traits like pagination, sorting, error handling, or rate limits. This is a significant gap for a tool with no annotation coverage, making it unclear how the tool behaves beyond basic listing.
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 with no wasted words. It is front-loaded with the core action ('List test plans') and context ('in a project'), making it easy to parse quickly. Every part of the description earns its place by conveying essential information succinctly.
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 lack of annotations and output schema, the description is incomplete. It does not explain what the tool returns (e.g., list format, fields included) or any behavioral aspects like pagination or errors. For a tool with no structured data beyond the input schema, this leaves critical gaps in understanding how 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?
The input schema has 100% description coverage, fully documenting both parameters ('projectKey' and 'limit'). The description does not add any meaning beyond what the schema provides, such as explaining the format of 'projectKey' or typical use cases for 'limit'. Baseline 3 is appropriate as the schema handles parameter documentation adequately.
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 ('test plans in a project'), making the tool's purpose understandable. However, it does not differentiate from sibling tools like 'get_test_info' or 'query_test_executions', which might also retrieve test-related data, leaving some ambiguity about its specific scope.
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 lacks context such as whether this is for browsing all test plans, if it's the primary retrieval method, or how it differs from siblings like 'get_test_info' or 'query_test_executions', leaving the agent without usage direction.
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 implies a write operation ('import') but doesn't specify permissions needed, whether it creates or updates records, error handling, or side effects. This is a significant gap for a tool with multiple parameters and no output schema.
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 and lists formats without unnecessary elaboration. Every word earns its place, making it easy to scan and understand quickly.
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?
For a tool with 6 parameters, no annotations, and no output schema, the description is incomplete. It lacks behavioral context, usage differentiation from siblings, and details on what happens after import (e.g., does it create test executions?). More information is needed to guide effective use.
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 adds no additional meaning beyond listing format names, which are already in the enum. Baseline 3 is appropriate as the 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 ('import') and resource ('automated test execution results'), and lists specific formats (JUnit, Cucumber, etc.), making the purpose explicit. However, it doesn't distinguish this tool from sibling tools like 'create_test_execution' or 'update_test_execution', which might handle similar test-related operations.
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 'create_test_execution' or 'update_test_execution'. The description only lists supported formats without indicating context or prerequisites, leaving the agent to guess based on parameter names alone.
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 full burden for behavioral disclosure but offers minimal information. It mentions 'query and filter' which implies a read-only operation, but doesn't address pagination behavior (beyond the limit parameter), rate limits, authentication requirements, or what happens when no results match filters. For a tool with 6 parameters and no annotation coverage, this is inadequate.
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 perfectly concise at just 6 words ('Query and filter test executions in Xray'). Every word earns its place by establishing the core action and resource. There's no wasted language, repetition, or 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?
For a query tool with 6 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what information is returned, how results are structured, whether the tool supports pagination beyond the limit parameter, or typical response formats. The agent would need to guess about the tool's behavior and outputs.
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 description coverage is 100%, so all parameters are well-documented in the schema itself. The description adds no additional parameter semantics beyond the generic 'query and filter' context. This meets the baseline expectation when schema documentation is comprehensive, but doesn't provide extra value like explaining relationships between parameters or special constraints.
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 with a specific verb ('query and filter') and resource ('test executions in Xray'), making it immediately understandable. However, it doesn't explicitly differentiate this query/filter tool from sibling tools like 'get_test_info' or 'get_test_plans', which prevents 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. With siblings like 'get_test_info' and 'get_test_plans' that might retrieve similar information, the agent receives no help in choosing between them. There's no mention of prerequisites, typical use cases, or exclusion criteria.
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 updating 'status and details' but does not cover critical aspects like required permissions, whether the update is reversible, potential side effects (e.g., if it triggers notifications or workflows), or error handling. This leaves significant gaps for a mutation 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, efficient sentence that directly states the tool's purpose without any fluff or redundancy. It is front-loaded with the core action and target, making it easy to parse quickly.
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 complexity of a mutation tool with no annotations and no output schema, the description is insufficient. It lacks information on behavioral traits (e.g., auth needs, side effects), usage context relative to siblings, and what the tool returns. This makes it incomplete for safe and effective agent use.
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 input schema fully documents all parameters, including descriptions and enum values for 'status'. The description adds no additional parameter semantics beyond implying that 'details' might include 'comment' and 'defects', but this is already clear from the schema. Baseline score of 3 is appropriate as the 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 action ('Update') and the target ('status and details of a test within an execution'), which is specific and actionable. However, it does not explicitly differentiate from sibling tools like 'execute_tests' or 'import_test_results', which might also involve test execution updates, leaving some ambiguity.
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. For example, it does not specify if this is for manual updates, post-execution status changes, or how it differs from 'execute_tests' or 'import_test_results'. This lack of context makes it harder for an agent to choose correctly among siblings.
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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