Provides tools to get comprehensive flaky tests data from Bitrise Insights, including options for specifying workspace, app, interval, duration, and detailed test cases.
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., "@Bitrise Insights MCP Server Get flaky tests for workspace 'my-workspace' for last month"
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 hacky bitrise insights mcp using playwright till Bitrise Insights API is released.
Clone the repository and build:
git clone https://github.com/naveen-bitrise/temp-bitrise-insights-mcp.git
cd temp-bitrise-insights-mcp
npm install
npx playwright install
npm run buildRelated MCP server: mcp-playwright-test
Add to your MCP client configuration:
{
"mcpServers": {
"bitrise-insights": {
"command": "node",
"args": ["dist/index.js"],
"cwd": "/path/to/temp-bitrise-insights-mcp",
"type": "stdio"
}
}
}Example for macOS/Linux:
{
"mcpServers": {
"bitrise-insights": {
"command": "node",
"args": ["dist/index.js"],
"cwd": "/Users/yourname/temp-bitrise-insights-mcp",
"type": "stdio"
}
}
}Example for Windows:
{
"mcpServers": {
"bitrise-insights": {
"command": "node",
"args": ["dist/index.js"],
"cwd": "C:\\Users\\yourname\\temp-bitrise-insights-mcp",
"type": "stdio"
}
}
}bitrise-insights-get-flaky-tests: Get comprehensive flaky tests data from Bitrise Insights
A browser window will open automatically when Bitrise login is required. Complete the login and the tool will continue automatically.
{
workspace_slug: string, // Required: Bitrise workspace slug
app_slug?: string, // Optional: Specific app slug
interval?: string, // Optional: hourly, daily, weekly, monthly (default: monthly)
duration?: string, // Optional: e.g. "july", "last week", "P6M" (default: P6M)
include_test_cases?: boolean, // Optional: Include detailed test cases (default: false)
specific_test?: { // Optional: Get details for specific test
test_case_name: string,
test_suite_name?: string
}
}"Get flaky tests for workspace 'my-workspace' for the last 6 months"
"Show me detailed test cases for app 'my-app' in workspace 'my-workspace'"
"Get builds data for test case 'LoginTest' in suite 'AuthSuite'"
Node.js 18+
Internet connection for browser authentication
git clone https://github.com/naveen-bitrise/temp-bitrise-insights-mcp.git
cd temp-bitrise-insights-mcp
npm install
npm run devMIT
Get comprehensive flaky tests data from Bitrise Insights including test cases and detailed test execution information: build IDs, run durations, pass/fail status, timestamps, branches, stacks, and commit hashes. Uses browser session authentication - a browser window will open automatically when login is required (specialized for flaky test analysis)
| Name | Required | Description | Default |
|---|---|---|---|
| app_slug | No | The Bitrise app slug (optional, for app-specific results) | |
| duration | No | Duration or specific time (e.g., "july", "last week", "P6M") | P6M |
| interval | No | Time interval (hourly, daily, weekly, monthly) | monthly |
| specific_test | No | Specific test to get comprehensive test run details for | |
| workspace_slug | Yes | The Bitrise workspace slug | |
| include_test_cases | No | Whether to include detailed test cases for each app |
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 explicitly warns that a browser window will open automatically when login is required, a critical side effect an agent must anticipate. It does not mention read-only semantics or rate limits, but the 'Get' verb implies a query and the authentication note is the most material behavior to disclose.
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, well-structured sentence that front-loads the tool's purpose before adding the authentication caveat. Every phrase earns its place: data scope and auth behavior are both essential for correct invocation. There is no filler, redundancy, or excessive detail.
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 output schema and no annotations, the description supplies key missing context: the exact data fields returned and the interactive authentication requirement. It does not detail the output shape, but the parameter schema covers input semantics. The overall context is sufficient for an agent to call it correctly.
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 six parameters. The description only loosely aligns with parameters via 'test cases' and 'test execution information', but it does not clarify the specific_test object or include_test_cases flags beyond the schema. The baseline of 3 is appropriate since the description adds little parameter-level meaning.
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 'Get comprehensive flaky tests data from Bitrise Insights' with a specific verb and resource, and enumerates concrete data fields (build IDs, run durations, pass/fail status, timestamps, branches, stacks, commit hashes). The phrase 'specialized for flaky test analysis' further distinguishes it from generic insights tools. No siblings are present, so no comparison is required.
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 does not explicitly name alternatives or exclusion criteria, but it clearly establishes the use case: flaky test analysis on Bitrise Insights. The 'specialized for flaky test analysis' phrase gives a clear context for when to invoke this tool. Since no sibling tools are provided, this level of guidance is sufficient.
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.
v0.1.0bitrise-insights-get-flaky-testsScored across 1 tool
Only one tool exists, so there is no possibility of confusing it with another tool. Its purpose is clearly limited to retrieving flaky test data.
The single tool name follows a clear action-oriented convention: bitrise-insights-get-flaky-tests. There is no mixed naming style or contradictory pattern to cause confusion.
A single tool is too few for a server named Bitrise Insights, which implies a broader analytics surface. While it may handle a narrow flaky-test workflow, it feels under-scoped.
The server only exposes flaky-test retrieval, with no tools for other Bitrise Insights data such as builds, test suites, trends, or general analytics. This is a significant coverage gap for the implied domain.
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