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524,225 tools. Updated 2026-09-06 14:34

"Vitest" matching MCP tools:

  • Execute Vitest tests with structured JSON output and optional log capture. Supports monorepos through workspace configuration. Set the project root before use and specify a test target to prevent full project runs.
    MIT
  • Run smoke tests before commit or deploy to confirm the project test suite passes. Auto-detects pytest, Jest, Vitest, or Mocha from project config and reports failures, with options to stop at the first error or target a specific suite.
    MIT
  • Generate test skeletons for source code with Jest, pytest, or vitest. Scaffold test stubs for untested public functions so you can begin testing a module without writing boilerplate.
    MIT
  • Run the project's vitest tests in a secure, fixed-argument shell with a 120s timeout and capped output. Restrict by test name or directory path to return pass/fail, exit code, and duration.
    MIT

Matching MCP Servers

  • Create a pending post-incident test from a lesson's attempt/gotcha, preserving provenance and returning the command to arm it as a sensor.
    Apache 2.0
  • Search Forge's stored patterns to find previously learned conventions, failure modes, and successful approaches for project guidance and debugging.
    MIT
  • Execute JavaScript to query Gaffer test and coverage data, analyze project health, debug failures, and identify untested code areas using codemode API functions.
    MIT
  • Execute commands in a terminal window, read structured output, and wait for patterns or quiet periods. Use 'run' for complete command execution with result.
    MIT
  • Execute commands in a desktop console and retrieve their output in one call. Read current screen text or send input with fine-grained control for incremental workflows.
    MIT
  • Query real GitHub migration data to identify which packages developers are switching from and to. Validate technology choices using ground-truth analysis of package.json and requirements.txt diffs.
    MIT
  • Save learned patterns like test commands and failure diagnostics to persistent memory for future project runs, preventing duplicate entries to maintain efficiency.
    MIT
  • Submit autonomous tasks for AI to execute continuously until completion criteria are met. Define purpose, desired outcomes, verifiable completion conditions, and project context.
    MIT
  • Analyze test coverage to identify untested lines, functions, branches, and statements. Get actionable insights and recommendations for improving coverage, with automatic exclusion of non-production files.
    MIT
  • Scaffold a production-ready Express.js + TypeScript backend project with your choice of ORM, Zod validation, Swagger docs, Docker, ESLint, Vitest, and more.
    MIT
  • Discover test files matching .test.* and .spec.* patterns recursively. Get structured file info with absolute and relative paths to understand test organization and coverage. Optionally limit search to a specific directory.
    MIT
  • Write and run tests for specified modules, files, or behaviors without modifying production code. Supports custom frameworks and run verification.
    MIT
    Destructive
  • Retrieve the current status and timing details of a previously submitted browser test job. Indicates if job is created, queued, executing, completed, or failed.
    MIT
  • Retrieve a complete test report for finished jobs, including step-by-step results, pass/fail summary, root-cause analysis, and UX improvement insights.
    MIT
  • Runs npm scripts such as test or lint and parses Vitest/Jest output into structured per-file pass/fail results, falling back to raw output for non-test scripts.
    MIT