ai-testing-mcp

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Model Context Protocol (MCP) server for comprehensive AI testing, evaluation, and quality assurance.

AI Testing MCP provides standardized testing methodologies, evaluation metrics, and automated testing workflows for AI/ML systems. It implements the Model Context Protocol for seamless integration with AI development tools.

• Unit Tests: Component-level testing
• Integration Tests: End-to-end workflow testing
• Performance Tests: Latency, throughput, resource usage
• Security Tests: Adversarial attacks, prompt injection
• Quality Tests: Output validation, consistency checks

• Accuracy: Precision, recall, F1 score
• Quality: Coherence, relevance, fluency
• Safety: Toxicity, bias detection
• Performance: Response time, token usage
• Cost: API costs, compute resources

• Standard Protocol: Implements MCP specification
• Tool Definitions: Testing tools for AI assistants
• Resource Management: Test data and configuration
• Prompt Templates: Reusable test prompts

# Clone the repository
git clone https://github.com/groovy-web/ai-testing-mcp.git
cd ai-testing-mcp

# Install dependencies
npm install

# Configure environment
cp .env.example .env
# Edit with your API keys

# Start the MCP server
npm start

# Use with MCP client
# Add server configuration to your MCP client

{
  "mcpServers": {
    "ai-testing": {
      "command": "node",
      "args": ["/path/to/ai-testing-mcp/dist/index.js"],
      "env": {
        "OPENAI_API_KEY": "your-key",
        "ANTHROPIC_