Testsprite Gateway

Testsprite Gateway is an MCP server that connects AI assistants to TestSprite's automated testing platform, enabling AI-driven test generation, execution, and failure analysis. This MCP bridge allows language models to read your code, understand your intent, generate appropriate test cases, run tests against your application, and provide specific feedback on what needs to be fixed when tests fail.

When to Use This MCP Server

Connect this server when...

• You want AI-generated test cases that understand your code's intent and automatically cover edge cases
• Your team needs automated test execution with intelligent failure analysis and fix suggestions
• You are adopting test-driven development and want AI assistance writing tests before implementation
• You need to increase test coverage across your codebase with minimal manual effort
• You want regression testing that automatically identifies which code changes broke existing functionality

Consider alternatives when...

• You only need a basic test runner without AI-driven test generation (use Jest, pytest, or similar directly)
• Your testing requirements are limited to manual QA workflows without automation
• You need performance or load testing rather than functional test generation

Quick Start

Copy
# .mcp.json configuration
{
  "mcpServers": {
    "testsprite": {
      "command": "npx",
      "args": ["@testsprite/testsprite-mcp@latest"],
      "env": {
        "API_KEY": "your-api-key"
      }
    }
  }
}

Connection setup:

1. Sign up at testsprite.com and obtain your API key from the dashboard
2. Ensure Node.js 18+ is installed on your system
3. Add the configuration above to your .mcp.json file with your API key
4. Restart your MCP client to connect to TestSprite

Example tool usage:

# Generate tests for a function
> Generate comprehensive unit tests for the calculateDiscount function in pricing.ts

# Run tests and analyze failures
> Run the test suite for the user authentication module and explain any failures

# Suggest fixes
> The login test is failing - analyze the output and suggest code fixes

Core Concepts

Concept	Purpose	Details
Intent Analysis	Code understanding	TestSprite reads your source code to understand intended behavior and generates tests that validate that intent
Test Generation	Automated test creation	AI-powered generation of unit tests, integration tests, and edge case tests based on code analysis
Test Execution	Automated running	Runs generated tests against your codebase and captures results including pass/fail status and output
Failure Analysis	Diagnostic feedback	Analyzes test failures to provide specific, actionable feedback on what code needs to change
Coverage Tracking	Completeness measurement	Monitors which code paths are exercised by tests and identifies untested areas for additional coverage

Architecture:

+------------------+       +------------------+       +------------------+
|  Your Codebase   |       |  TestSprite MCP  |       |  AI Assistant    |
|  Source Files     |------>|  Server (npx)    |<----->|  (Claude, etc.)  |
|                  |       |  + TestSprite API | stdio |                  |
+------------------+       +------------------+       +------------------+
                                  |
                                  v
                           +------------------+
                           |  Test Results    |
                           |  + Fix Guidance  |
                           +------------------+

Configuration

Parameter	Type	Default	Description
API_KEY	string	(required)	TestSprite API key for authentication and access to test generation services
test_framework	string	(auto-detect)	Override the detected test framework (jest, mocha, pytest, vitest)
source_dir	string	./	Root directory of the source code to analyze for test generation
output_dir	string	tests	Directory where generated test files are written
coverage_threshold	integer	80	Minimum code coverage percentage target for generated test suites

Best Practices

1. Start with critical business logic. Rather than generating tests for the entire codebase at once, focus on the most critical functions first. Payment processing, authentication, data validation, and core business rules should be tested thoroughly before moving to less critical utility functions.

2. Review generated tests before committing. AI-generated tests capture the AI's understanding of your code's intent, which may not always match your actual requirements. Review each test to verify the assertions match expected behavior and the test names clearly describe what they validate.

3. Use failure analysis to improve both tests and code. When TestSprite reports test failures, evaluate whether the failure indicates a bug in the code or an incorrect test assumption. The failure analysis often reveals subtle edge cases that deserve attention regardless of whether the test or code needs adjustment.

4. Integrate test generation into your CI pipeline. Configure TestSprite to run as part of your continuous integration process. This ensures new code changes are automatically tested and regressions are caught before merging. The AI can generate tests for new functions added in pull requests.

5. Maintain a coverage baseline and track trends. Set a coverage threshold and monitor it over time. The coverage tracking capabilities help identify areas of the codebase that are under-tested and direct test generation efforts where they provide the most value.

Common Issues

"API key invalid" when connecting. Verify your TestSprite API key is correctly configured in the environment variables. Check your TestSprite dashboard to confirm the key is active and has not been regenerated since you configured it.

Generated tests import incorrect modules. TestSprite infers import paths from your project structure, but complex module resolution configurations (TypeScript path aliases, webpack aliases) may not be detected automatically. Specify the source_dir and adjust imports in generated tests as needed.

Test execution timeout on large test suites. Running extensive test suites through the MCP server can exceed default timeout limits. Break large test runs into smaller targeted suites by specifying individual modules or test files rather than running the entire suite at once.