Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP DevOps Test Server List tests in the WebApp Testing project"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A Model Context Protocol (MCP) server implementation for DevOps Test, enabling test execution and management through standardized MCP clients.
Retrieve projects from the Test system
List tests from specific projects with optional filtering
Execute tests in projects with browser selection
Monitor test execution results and status
Download and analyze test logs from execution archives
Related MCP server: testing-mcp
This MCP server is provided "as is" without any warranties. It is designed to work with the DevOps Test system and may require specific configurations to function correctly. Users are responsible for ensuring compatibility with their Test instance. This server provides test execution functionality, the author is not liable for any issues arising from test execution or system interactions.
Scenario: You're a QA engineer who needs to execute a suite of tests across different projects and monitor their results.
Steps:
"Get me all available projects in the Test system"
"Show me all tests in the 'WebApp Testing' project"
"Execute the 'LoginFunctionalityTest' in the WebApp Testing project using Chrome browser"
"Check the results of the test execution and get the detailed report"
"Download the test logs for further analysis"
Benefits: Streamline test execution and monitoring without manual interface interaction.
Scenario: You need to validate functionality across different browsers for a critical release.
Steps:
"List all UI tests in the 'E-commerce Platform' project"
"Execute the 'CheckoutProcessTest' using Edge browser"
"Monitor the test results and wait for completion"
"Execute the same test using Chrome browser for comparison"
"Download logs from both executions to compare results"
Benefits: Efficiently coordinate cross-browser testing and result comparison.
Scenario: You're monitoring test results as part of a CI/CD pipeline and need real-time status updates.
Steps:
"Get all projects and identify the relevant test project"
"List tests of type 'EXT_TEST_SUITE' for automated test suites"
"Execute critical test suites for the latest build"
"Continuously monitor test execution status until completion"
"Retrieve comprehensive test results and logs for CI reporting"
Benefits: Integrate test execution monitoring into automated workflows and CI/CD pipelines. 4. "Create a dependent task 'Integrate user profile API' in the 'Frontend' component" 5. "Check work items assigned to backend team members to see their current workload"
Benefits: Coordinate cross-functional work and ensure proper dependency tracking.
The server requires configuration for authentication and connection to your Test instance. You can provide configuration in several ways:
Create a .env file in the project root and add your configuration values:
# Copy the example below and fill in your actual values
TEST_ACCESS_TOKEN=your_base64_encoded_token_here
TEST_SERVER_URL=https://your-test-server.com/test
TEST_TEAMSPACE_ID=your-teamspace-id-here
TEST_INSECURE_TLS=falseSet the following environment variables:
export TEST_ACCESS_TOKEN="your_base64_encoded_token_here"
export TEST_SERVER_URL="https://your-test-server.com/test"
export TEST_TEAMSPACE_ID="your-teamspace-id-here"
export TEST_INSECURE_TLS="false"Pass configuration as command line arguments:
node src/lib/server.js --token "your_token" --server-url "https://your-server.com/test" --teamspace-id "your-teamspace-id"If your Test server uses a self-signed or otherwise untrusted certificate, add --insecure-tls to disable certificate validation for this process only:
node src/lib/server.js --token "your_token" --server-url "https://your-server.com/test" --teamspace-id "your-teamspace-id" --insecure-tlsCreate a .env file in the project root with your values:
# Create .env file with your actual configuration values
TEST_ACCESS_TOKEN=your_base64_encoded_token_here
TEST_SERVER_URL=https://your-test-server.com/test
TEST_TEAMSPACE_ID=your-teamspace-id-here
TEST_INSECURE_TLS=falseParameter | Environment Variable | Command Line Argument | Required | Default | Description |
Access Token |
|
| ✅ Yes | None | Base64 encoded personal access token for authentication |
Server URL |
|
| ✅ Yes | None | URL to your Test server instance |
Teamspace ID |
|
| ✅ Yes | None | Your Test teamspace identifier |
Insecure TLS |
|
| No |
| Disable TLS certificate validation for self-signed or untrusted server certificates |
Note: The server now uses a simplified authentication system that calls the /rest/tokens endpoint instead of Keycloak. This requires only your personal access token for authentication.
Security note: Only enable insecure TLS for trusted internal environments. It disables HTTPS certificate verification for the MCP server process.
Node.js >= 18.0.0
npm or yarn package manager
You can run the MCP server directly without installation:
npx @securedevops/mcp-devops-test --token "your_token" --server-url "https://your-server.com/test" --teamspace-id "your-teamspace-id"For self-signed certificates:
npx @securedevops/mcp-devops-test --token "your_token" --server-url "https://your-server.com/test" --teamspace-id "your-teamspace-id" --insecure-tlsnpm install -g @securedevops/mcp-devops-test
mcp-devops-test --token "your_token" --server-url "https://your-server.com/test" --teamspace-id "your-teamspace-id"For development or customization:
# Clone the repository
git clone https://github.com/securedevops/mcp-devops-test.git
cd mcp-devops-test
# Install dependencies
npm install
# Create configuration file (see Configuration section below)
# Create .env file with your configuration values
# Start the MCP server
npm startAdd the following to your Claude Desktop MCP configuration:
{
"mcpServers": {
"devops-test": {
"command": "npx",
"args": [
"@securedevops/mcp-devops-test",
"--token", "your_token_here",
"--server-url", "https://your-server.com/test",
"--teamspace-id", "your_teamspace_id"
]
}
}
}{
"mcpServers": {
"devops-test": {
"command": "npx",
"args": ["@securedevops/mcp-devops-test"],
"env": {
"TEST_ACCESS_TOKEN": "your_token_here",
"TEST_SERVER_URL": "https://your-server.com/test",
"TEST_TEAMSPACE_ID": "your_teamspace_id",
"TEST_INSECURE_TLS": "false"
}
}
}
}Add the following to your Claude Desktop MCP configuration:
{
"mcpServers": {
"devops-test": {
"command": "node",
"args": ["/path/to/mcp-devops-test/src/lib/server.js"],
"env": {
"TEST_ACCESS_TOKEN": "your_token_here",
"TEST_SERVER_URL": "https://your-server.com/test",
"TEST_TEAMSPACE_ID": "your_teamspace_id",
"TEST_INSECURE_TLS": "false"
}
}
}
}Or with command line arguments:
{
"mcpServers": {
"devops-test": {
"command": "node",
"args": [
"/path/to/mcp-devops-test/src/lib/server.js",
"--token", "your_token_here",
"--server-url", "https://your-server.com/test",
"--teamspace-id", "your_teamspace_id",
"--insecure-tls"
]
}
}
}The MCP DevOps Test server provides the following tools for interacting with DevOps Test:
get_projectsPurpose: Retrieves all projects from the Test system Parameters: None Usage: Use this to get a list of all available projects in your Test instance. This is typically the first step to understand what projects you can work with for test execution.
list_testsPurpose: Retrieves tests from a specific project with optional test type filtering Parameters:
projectId (string): The ID of the project to retrieve tests from
testType (string, optional): Optional test type filter (e.g., EXT_TEST_SUITE, EXT_TEST_SCPT, EXT_TEST_LOADP, EXT_TEST_STUB, etc.)
branch (string, optional): Branch to use for retrieving tests (default: main)
Usage: Once you have a project ID, use this to see all tests within that project. You can filter by specific test types if needed.
execute_testPurpose: Execute a test in a specific project by test name Parameters:
projectId (string): The ID of the project containing the test
testName (string): The name of the test to execute
browserName (string, optional): Browser to use for execution (default: edge)
revision (string, optional): Revision to use (default: main)
Usage: Execute a specific test within a project. Tests typically take 60-180 seconds to complete.
Important: After execution, wait at least 60 seconds before checking results, then use progressive back-off for status checks.
get_test_resultsPurpose: Get comprehensive test execution results and report data Parameters:
projectId (string): The ID of the project containing the test
resultId (string): The result ID from the test execution
executionId (string, optional): Optional execution ID for additional context
Usage: Monitor test execution progress and retrieve detailed results. Use progressive polling if status is RUNNING: 30s → 45s → 60s → 90s between checks.
get_test_log_resultsPurpose: Download and analyze test log results from the zip archive Parameters:
projectId (string): The ID of the project containing the test
downloadId (string): The download ID for the result archive (from test execution results)
Usage: Download detailed test logs and artifacts from completed test executions for further analysis and debugging.
Execute a test in a specific project by test name. TIMING: Tests typically take 60-180 seconds to complete. AGENT BEHAVIOR: After execution, inform user 'Test started, will complete in ~2 minutes', then wait at least 60 seconds before first status check. Use progressive back-off for subsequent checks: 30s → 45s → 60s → 90s intervals until completion.
| Name | Required | Description | Default |
|---|---|---|---|
| tags | No | Optional labels/tags to assign to the test execution (e.g., ["label1", "label2"]) | |
| revision | No | Revision to use (default: main) | main |
| testName | Yes | The name of the test to execute | |
| projectId | Yes | The ID of the project containing the test | |
| variables | No | Optional variables to pass to the test execution as key-value pairs (e.g., {"abc": "xyz"}) | |
| browserName | No | Browser to use for execution (default: edge) | edge |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses timing expectations (60-180 seconds) and prescribes agent behavior (inform user, wait intervals, back-off strategy). This adds significant behavioral context beyond the schema, though it does not describe return values or failure handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, with clear TIMING and AGENT BEHAVIOR sections. Every sentence contributes useful information, and the format aids readability and comprehension. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers timing and polling behavior well, but lacks information about the tool's return value or how subsequent status checks are performed (e.g., via sibling tools). Since there is no output schema, this gap affects completeness. Overall, it is adequate but leaves room for improvement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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. The description adds minimal value by referencing 'test name' and 'specific project', but does not provide additional semantic depth beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Execute a test in a specific project by test name.' The verb 'execute' and resource 'test in project' are specific, and the sibling tools (get_test_results, list_tests, etc.) are clearly different in function, so this tool is well-distinguished.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 (to execute a test), but does not explicitly mention alternatives or exclusions. It focuses on operational behavior rather than comparing with siblings, which earns a 4 rather than 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieves all projects from the Test system
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It implies a read-only, non-destructive operation via the verb 'Retrieves,' but it does not mention any side effects, permissions, pagination, or whether the returned data is a list or collection. The minimal transparency is sufficient for such a simple tool but lacks richer context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no redundant words. It states exactly what the tool does without filler, achieving maximum conciseness for a tool of this simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no parameters, no output schema, and no annotations, the description adequately explains the basic function. It tells the agent that this is a read-only fetch of all projects. It could optionally mention the return format (e.g., 'returns a list of projects'), but given the lack of complexity, the current description is nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema coverage is trivially 100%. Per the baseline rule for 0-parameter tools, the description does not need to add parameter details. The description correctly focuses on the action and scope, requiring no additional parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Retrieves') and resource ('all projects'), with a scope qualifier ('from the Test system'). It is immediately distinguishable from sibling tools, which all focus on tests and execution rather than project listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 vs alternatives. While sibling tools are clearly test-related, the description does not explicitly state any usage context, exclusions, or alternative conditions. The tool is self-explanatory by name, but the description adds no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Download and analyze test log results from the zip archive
| Name | Required | Description | Default |
|---|---|---|---|
| projectId | Yes | The ID of the project containing the test | |
| downloadId | Yes | The download ID for the result archive (e.g., from result execution) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description carries full responsibility for behavioral disclosure. It says 'Download and analyze' but does not clarify whether the operation is read-only, consumes the archive, or has side effects, leaving significant uncertainty.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence of nine words, front-loaded with the action and object, containing no filler or redundant details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description should explain return values, but it does not. It also lacks usage conditions or differentiation from the sibling get_test_results, making the tool incomplete for an agent to fully understand.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 100% coverage with descriptions for both projectId and downloadId. The description adds the context of a zip archive, aligning with downloadId, but does not add meaningful parameter-specific semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Download and analyze' with a clear resource 'test log results from the zip archive'. It distinguishes from siblings like get_test_results by specifying 'log' results and the zip archive source, though the meaning of 'analyze' could be more precise.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives such as get_test_results or prepare_test_download. There is no mention of prerequisites, exclusions, or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get comprehensive test execution results and report data. PROGRESSIVE POLLING: If status is RUNNING, wait using progressive back-off: 30s → 45s → 60s → 90s between checks. Tests typically complete in 60-180 seconds.
| Name | Required | Description | Default |
|---|---|---|---|
| resultId | Yes | The result ID from the test execution | |
| projectId | Yes | The ID of the project containing the test | |
| executionId | No | Optional execution ID for additional context |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses progressive polling back-off and typical duration, which are important behavioral traits. However, it does not describe return structure, error cases, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, purpose leading, then specific behavioral guidance. Every sentence earns its place with no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and full schema coverage, the description provides sufficient context. It could mention return states or limits, but the polling guidance adds meaningful context beyond a basic 'get'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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. The description adds no parameter-specific information, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves comprehensive test execution results and report data, using a specific verb and resource. However, it does not explicitly differentiate from sibling tool get_test_log_results, so it 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.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit polling guidance for when status is RUNNING and gives expected completion time. This is clear context for use, though it does not mention when not to use this tool or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieves tests from a specific project with optional test type filtering
| Name | Required | Description | Default |
|---|---|---|---|
| branch | No | Branch to use for retrieving tests (default: main) | main |
| testType | No | Optional test type filter (e.g., EXT_TEST_SUITE, EXT_TEST_SCPT, EXT_TEST_LOADP, EXT_TEST_STUB, etc.) | |
| projectId | Yes | The ID of the project to retrieve tests from |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only states that tests are retrieved, without mentioning pagination, ordering, error conditions, or the meaning of the branch parameter. This is minimal behavioral detail for an AI agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the core action and resource, containing no filler or redundant detail. It is maximally concise while remaining informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, but the description lacks details such as the return format, whether branch affects test selection, and any usage context. With no annotations or output schema, the description is adequate but leaves gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides complete descriptions for all three parameters (100% coverage), so the baseline is 3. The description adds no new semantic information beyond restating that testType filtering is optional, which the schema already conveys.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves tests from a specific project with optional filtering, using the specific verb 'Retrieves' and naming the resource. It does not explicitly distinguish from sibling tools like get_test_results, but the function is unambiguous and aligns with the tool name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus sibling tools such as get_test_results or prepare_test_download. The mention of optional test type filtering implies a use case but provides no explicit context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Prepare test result download and extract download ID from location header
| Name | Required | Description | Default |
|---|---|---|---|
| resultId | Yes | The result ID from the test execution | |
| projectId | Yes | The ID of the project containing the test |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavior. It mentions extracting an ID from the location header, but does not clarify side effects, async behavior, success/failure implications, or what the returned ID represents. The single behavioral detail is insufficient for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the core purpose. It avoids unnecessary words, though it packs two actions (prepare and extract) into one sentence, making it slightly dense.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has two required parameters and no output schema, so the description should explain what the caller receives and how to use the extracted download ID. It does not state the return format, whether the download is asynchronous, or how to retrieve the actual file. The 'location header' mention assumes HTTP knowledge not provided elsewhere.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both projectId and resultId having clear descriptions. The tool description adds no additional parameter meaning, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Prepare') and resource ('test result download'), and adds a distinguishing detail about extracting a download ID from the location header. This separates it from sibling tools like get_test_results, though the exact output behavior remains somewhat unclear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance is provided. The description implies use for downloading test results, but does not explain relationships with sibling tools or conditions under which this tool should be preferred over alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v0.3.20execute_testget_projectsget_test_log_resultsget_test_resultslist_testsprepare_test_downloadMost tools have clearly distinct purposes: projects, tests, execution, results, logs, and download preparation. The only potential confusion is between get_test_results and get_test_log_results, but their descriptions differentiate comprehensive report data from log archive analysis.
Tool names follow a consistent verb_noun pattern (get_, list_, execute_, prepare_) and all use snake_case. Minor inconsistency exists between get_ and list_ for retrieval operations, but this is a common and acceptable variation.
With 6 tools, the server is well-scoped for a DevOps test management workflow: project discovery, test listing, execution, result retrieval, log retrieval, and download preparation. Each tool serves a distinct step without unnecessary redundancy.
The tool set covers the core lifecycle of test execution: discover projects, list tests, execute tests, retrieve results, and download logs. Minor gaps exist (e.g., no explicit test detail view, no cancellation mechanism), but agents can accomplish primary workflows without dead ends.
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