TestRail MCP Server

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.0.0
Disambiguation5/5
Each tool targets a distinct resource (project, suite, test case, test run, test result) with a clear action (list, get, create, update, close, add). There is no overlap between list/get variants or between action verbs.
Naming Consistency5/5
Tool names consistently follow a list_/get_ prefix for read operations and specific action verbs (create, add, update, close) for mutations, all in lowercase snake_case. The pattern is uniform and predictable.
Tool Count5/5
13 tools is well within the ideal range for a domain-specific server, covering all major TestRail entities (projects, suites, test cases, runs, results) without unnecessary redundancy or bloat.
Completeness3/5
The core workflow of creating runs, adding results, and closing runs is covered, but there are notable gaps: no create/delete for test cases or suites, and no generic get_project by ID. This limits full lifecycle management of test assets.
Average 3.4/5 across 13 of 13 tools scored. Lowest: 1.9/5.
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 is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

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 of explaining behavioral traits. It does not disclose whether updates are partial or full replacement, how non-existing case IDs are handled, or any error/response behavior. The description is purely declarative with no transparency into side effects or limits.
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 under-specified and does not earn its place. It adds no information beyond the tool name. This is under-specification rather than concise, valuable content.
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?
For a mutation tool with no annotations and no output schema, the description should explain update semantics, error conditions, and response handling. It provides none of this. The schema covers parameters but not behavioral context, leaving the tool significantly incomplete for an agent to invoke correctly.
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 fully documents each parameter (e.g., optional nature, priorities, automation ID). The description adds no extra parameter information. Baseline is 3 because the schema does the heavy lifting, and the description neither enhances nor contradicts it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Update a test case with new information' essentially restates the tool name 'update_test_case' without adding specific scope or behavioral detail. It does not mention which fields can be updated or how it differs from other tools. While it is a clear verb+resource, the lack of any additional context makes it tautological.
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 creating a test run or getting test case details. There is no mention of prerequisites, typical use cases, or when not to use it. The sibling list is not leveraged to differentiate 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, the description carries the full burden of disclosing behavior, but it only states a simple getter. It does not mention whether the operation is read-only, requires authentication, or what 'configured' means, nor does it describe the return format or any potential side effects.
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 front-loads the action and object with no unnecessary words. It is highly scannable and effective for a simple getter tool.
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?
The description is minimal and omits essential context: what 'configured project' refers to, what 'details' includes, and any return value structure (no output schema exists). For a tool with no parameters and no annotations, the description should clarify these points to allow correct invocation and interpretation.
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, so the description cannot add parameter meaning. Baseline is 4 for no parameters, which is appropriate here.
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 uses a specific verb 'Get' and a clear resource 'TestRail project details', clearly indicating the tool retrieves project information. However, it does not explicitly distinguish itself from sibling tools like list_projects, leaving some ambiguity about what 'configured' means in contrast to listing all projects.
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 such as list_projects or get_suite. The description simply states what it does without mentioning any exclusions, prerequisites, or preferred contexts.
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. 'Create' implies a write operation, but no details are given about required permissions, side effects, idempotency, or what 'configured project' means. The description is too sparse to cover these aspects.
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 of eight words. It conveys the essential purpose without unnecessary elaboration, earning a high score for 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?
The tool is a simple create operation with full schema documentation, but the description lacks guidance on return values (no output schema exists) and clarifies the ambiguous 'configured project'. It is minimally viable but has clear gaps in contextual information.
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%, with all four parameters (name, case_ids, suite_id, description) adequately described. The description itself adds no parameter-level information, so the baseline score of 3 is appropriate.
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 ('Create') and names the resource ('test run') within a clear context ('configured TestRail project'). It clearly distinguishes from sibling tools like list_test_runs or close_test_run by indicating a creation action.
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 is provided. The description does not mention related operations like add_test_results or update_test_case, leaving the agent to infer usage solely from the tool name and generic description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only states the action 'Get a specific test run by ID' without mentioning read-only nature, return format, error handling, or permissions, leaving the agent without critical 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 sentence with zero filler or redundancy. It is appropriately sized for a simple get-by-ID tool and is front-loaded with the action verb and resource.
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?
For a simple get-by-ID tool with no output schema, the description is minimal but adequate in stating the core operation. However, it omits any detail about return value, error conditions, or usage context, leaving some ambiguity given the lack of output schema and annotations.
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 already fully describes run_id as 'The ID of the test run' (100% schema description coverage). The description's mention of 'by ID' adds no additional parameter semantics beyond the schema, so baseline of 3 is appropriate.
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 'Get a specific test run by ID' uses a specific verb (Get) and clearly identifies the resource (test run) and selection method (by ID). This distinguishes it from sibling list_test_runs, which retrieves a collection, and other tools.
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 vs. alternatives like list_test_runs. It does not state that this is for retrieving a single known run while list_test_runs is for browsing multiple runs, nor does it mention any prerequisites or conditions.
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. It only states the add action and repeats status IDs from the schema. It does not disclose whether existing results are overwritten, whether the test run must be in a certain state, or what the function returns on success.
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 with an important status ID mapping appended. It is concise, front-loaded, and every part serves a purpose without wasted words.
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?
For a tool with two parameters and a complete schema, the description is functional. However, it lacks critical context for a write operation: no information about side effects, prerequisites, or response behavior, which makes it incomplete for an agent deciding whether to invoke it.
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 100% with detailed descriptions for all parameters, including the status ID mapping. The description adds minimal extra value by mentioning 'multiple test cases' and listing status IDs, but the schema already documents these details.
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 'Add' plus resource 'test results' and clarifies scope 'multiple test cases in a test run'. This clearly distinguishes from sibling tools such as get_test_results, which reads results.
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 adding test results, but it does not explicitly state when to use it over alternatives or provide any exclusions. Sibling tools like get_test_results exist for reading, but no comparison is made.
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, the description carries full burden for behavioral disclosure. It only states the effect ('marks it as completed') but does not disclose potential side effects, error conditions (e.g., if the run is already closed), or permissions required. For a state-changing tool, this is a significant 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 concise sentence that front-loads the key action and outcome. Every word earns its place, with no redundancy or irrelevant detail.
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 tool has low complexity (one parameter, no output schema) and the description covers the basic purpose. However, it lacks information about what happens on success or failure, and whether there are any constraints. It is adequate but minimal.
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 for run_id ('The ID of the test run to close'), so the schema fully explains the parameter. The tool description adds no additional parameter information, but the baseline of 3 is appropriate given the schema coverage.
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 ('close') and resource ('test run'), and clarifies that closing marks it as completed. It clearly distinguishes from sibling tools like create_test_run, list_test_runs, and get_test_run, which involve different actions.
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 a test run should be marked as completed, but it does not explicitly state when to use this tool versus alternatives, nor mention any prerequisites such as the run needing to be open or results being added first. There is no explicit context 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 full responsibility for behavioral disclosure. It only states the action 'Get' (read), but does not mention potential errors (e.g., if ID not found), authentication requirements, or return format. For a simple getter, this is insufficient 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, concise sentence that is front-loaded with the verb and resource. It contains no redundant words or unnecessary details, earning a perfect score for conciseness and structure.
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 tool is a simple get-by-ID operation, and the schema fully documents the parameter. However, with no output schema or annotations, the description does not explain the return value or error behavior. It is adequate but leaves gaps that could affect an agent's confidence in using it correctly.
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%, with parameter 'case_id' clearly described as 'The ID of the test case'. The description's 'by ID' adds no new meaning beyond what the schema provides, so a baseline of 3 is appropriate.
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 'Get a specific test case by ID' uses a specific verb ('Get') and resource ('test case') with a clear identifier ('by ID'). It clearly distinguishes from sibling tools such as list_test_cases (which lists multiple) and update_test_case (which modifies).
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 use when a single test case is needed by ID, but it does not explicitly state when to use this tool versus alternatives. No exclusions or alternative tool names are mentioned, leaving the usage context implicit.
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. It discloses the basic list/filter behavior but does not mention whether it is read-only, how pagination works, what fields are returned, or any authentication/prerequisite expectations. For a list operation, this is a significant 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 concise and front-loaded: it states the primary function in the first sentence and the optional parameter in the second. Every word earns its place.
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?
For a simple tool with one optional parameter and no output schema, the description is minimally adequate but lacks important context: what the returned test runs look like, any default behavior, and when to prefer this over get_test_run. Sibling information is available but not referenced.
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%, and the description restates the only parameter ('Optionally filter by suite_id') without adding new meaning. The schema already provides the type and description, so the description adds marginal value.
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 identifies the action ('Get test runs') and the resource ('for the configured project'). It distinguishes the tool from siblings like list_projects and list_suites, and the optional filter by suite_id adds specificity.
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 retrieving multiple test runs, but does not explicitly contrast with get_test_run or other siblings. The mention of 'configured project' gives some context, but no exclusions or alternative recommendations are provided.
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 only states the operation without mentioning potential return structure, ordering, pagination, or any assumptions about the 'configured project'.
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 wasted words. Every word contributes to understanding the tool's purpose.
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 parameterless list operation with no output schema, the description is reasonably complete. It could clarify what 'configured project' means, but the core operation is unambiguously stated.
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, so per rubric the baseline is 4. The description adds no parameter-specific meaning because none exist; the schema confirms an empty property set.
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's function with a specific verb ('Get') and resource ('all test suites'), scoped to 'the configured project'. It distinguishes from sibling tools like get_suite (singular) and list_test_cases (different resource type).
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, such as get_suite for a single suite or list_test_cases for test cases. The description implies usage but does not specify exclusions or preferred contexts.
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 burden of conveying safety. The verb 'Get' implies a read-only operation, but the description does not disclose error behavior (e.g., 404 if not found), response format, or any other behavioral traits. This is minimal but acceptable for a simple retrieval.
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, clear sentence with no filler. It is efficient and front-loaded with the verb and object.
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-ID operation with one parameter and no output schema, the description is adequate. It tells the agent what the tool does and what input is required. It could benefit from a note about what is returned or how to handle missing IDs, but overall it is sufficiently complete.
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 fully describes the one parameter, suite_id, as 'The ID of the suite.' The description repeats this without adding additional meaning. Since schema coverage is 100%, the baseline is 3.
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 action ('Get') and the resource ('a specific test suite'), with the scope ('by ID'). This distinguishes it from list_suites, which retrieves multiple suites. It follows the same pattern as get_project and get_test_case, making its purpose unambiguous.
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 does not explicitly state when to use this tool versus alternatives like list_suites or get_test_case. There is no mention of prerequisites or exclusions. The usage is implied by the get-by-ID pattern, but no direct guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the operation is a read ('Get') and that it returns all results for a run, but does not mention behaviors such as empty result handling, potential large payloads, or ordering. It is not misleading but lacks depth.
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 sentence efficiently conveys the tool's purpose with no redundant words. It is appropriately sized and front-loaded, earning its place.
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?
The tool is simple with one fully described parameter and no output schema. The description is sufficient for basic usage, though it could benefit from context about when results are available (e.g., after test run completion) or their structure. Still, it is complete for a straightforward read 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?
The input schema fully documents the single parameter 'run_id' with a description, and the tool description does not add additional semantics beyond referencing the test run. The high schema coverage (100%) warrants the baseline score.
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 retrieves all test results for a test run, using the specific verb 'Get' and resource 'test results'. It distinguishes itself from sibling tools like get_test_run (which retrieves run metadata) and add_test_results (which adds results).
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?
No explicit guidance is provided on when to use this tool versus alternatives. The purpose implies it is for retrieving results after a run, but there are no direct comparisons, exclusions, or prerequisites mentioned.
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, the description carries the full burden. It does not disclose pagination, ordering, permissions, or any side effects (though likely none). 'Get all' is simple, but the absence of additional behavioral context leaves the agent uncertain about response shape or system limits.
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, directly front-loaded sentence with no filler or repetition. Every word adds meaning.
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 0-param list tool with no output schema, the description is largely sufficient. It clearly states resource and scope. It could mention return type or hidden constraints, but the simplicity makes it near-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 tool has zero parameters, so the schema is trivially complete. The description adds no parameter info because none is needed. Baseline 4 is appropriate given the 0-param context.
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 'Get all TestRail projects' clearly states a specific action (get) on a specific resource (projects) with a scope ('all'). It strongly distinguishes from siblings like get_project (singular) and list_suites (different resource).
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: call this to retrieve all projects. However, it does not explicitly contrast with get_project or mention when to choose this over other listing tools. The guidance is inferred from the resource naming but not stated.
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 does not explicitly state that the operation is read-only, mention pagination or ordering, or describe what the response contains. 'Get' implies a read, but the description lacks details beyond the basic action.
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 short sentences, front-loaded with the core purpose and followed by the optional filter. Every word earns its place; no unnecessary details or fluff.
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 list tool with one optional parameter and no output schema or annotations, the description is fairly complete. It states the scope and filter, and the siblings provide context for when to use it. It could mention return format or pagination, but these are minor gaps given the tool's simplicity.
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 already provides 100% coverage for the single parameter (suite_id with description), so baseline is 3. The description repeats 'Optionally filter by suite_id' without adding any extra meaning beyond the schema.
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 action ('Get test cases') and the resource ('for the configured project'), distinguishing it from siblings like get_test_case (singular) and list_suites (suites). The optional filter by suite_id adds specificity without confusion.
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 for when to use the tool (listing test cases for the configured project) and mentions the optional filter. However, it does not explicitly exclude alternatives like get_test_case for individual retrieval, though the naming implies the distinction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![mcp-testrail MCP server](https://glama.ai/mcp/servers/yshpyluk/mcp-testrail/badges/card.svg)](https://glama.ai/mcp/servers/yshpyluk/mcp-testrail)

Score Badge

Copy to your README.md:

[![mcp-testrail MCP server](https://glama.ai/mcp/servers/yshpyluk/mcp-testrail/badges/score.svg)](https://glama.ai/mcp/servers/yshpyluk/mcp-testrail)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/yshpyluk/mcp-testrail'

If you have feedback or need assistance with the MCP directory API, please join our Discord server