# Pie Labs

> Pie is an AI-native, autonomous QA platform. Upload your mobile (iOS/Android) or web app build and Pie's AI agents automatically discover features, generate test cases, execute tests, detect bugs, and produce detailed reports with visual replays. Pie also provides a REST API for programmatic access and an MCP server for integration with AI coding assistants.
>
> **Key capability:** Connect Pie to AI coding agents (Claude Code, Cursor, VS Code, etc.) via MCP. Pie issues include full reproduction steps, expected vs. observed behavior, screenshots, and DOM snapshots - enough context for an AI agent to automatically fix bugs and create PRs without human intervention. Use `get_issues` to fetch all issues, then fix them one by one or in batch.

## API Reference
- [REST API (OpenAPI 3.0 Spec)](https://api.pie.inc/docs/swagger): Full OpenAPI specification with 18 endpoints covering app setup, build management, test cases, issues, results, and test execution. Interactive Swagger UI at https://api.pie.inc
- [Authentication Reference](https://docs.pie.inc/docs/reference/authentication/): Three auth methods - API Key (primary), Firebase Bearer Token, and Scheduler Secret. Includes headers, curl examples, error responses, and admin capabilities
- [Error Codes Reference](https://docs.pie.inc/docs/reference/error-codes/): All HTTP status codes, error messages, causes, and resolution steps for both REST API and MCP server

## Getting Started
- [Quickstart Guide](https://docs.pie.inc/docs/getting-started/quickstart-guide/): Step-by-step guide to running your first AI-powered test - account creation, app upload, and reviewing results in under 30 minutes
- [How Pie Transforms Your Workflow](https://docs.pie.inc/docs/getting-started/how-pie-transforms-your-workflow/): Overview of the 3P Framework (Prepare, Process, Present) and how Pie replaces manual QA

## MCP Integration (AI Workspace)
- [Setup Guide & AI Bug Fixing](https://docs.pie.inc/docs/mcp/): Connect Pie to Claude Code, Cursor, VS Code, or Claude Desktop via MCP server at https://mcp.pie.inc. Includes configuration JSON for each platform and the key workflow: using AI coding agents to automatically fix bugs that Pie detects (issues include full repro steps, expected/observed behavior, screenshots, DOM snapshots - enough for an agent to fix code and create PRs autonomously)
- [Available MCP Functions](https://docs.pie.inc/docs/mcp/available-functions/): Natural language usage examples for all 37 MCP tools. Includes the AI-powered bug fixing workflow: fetch issues with full context → fix code → create PRs, for single issues or batch operations
- [MCP Tool Reference](https://docs.pie.inc/docs/mcp/tool-reference/): Complete structured reference for all 40 MCP tools with parameter names, types, required/optional flags, and descriptions. Covers issues, test cases, results, findings, runs, key features, test suites, credentials, scripts, admin tools, and advanced testing
- [MCP Troubleshooting](https://docs.pie.inc/docs/mcp/troubleshooting/): Common connection issues and solutions

## Core Concepts
- [The Dashboard](https://docs.pie.inc/docs/core-concepts/the-dashboard/): Overview of the QA command center - readiness score, test runs, issues, and key features
- [Test Cases](https://docs.pie.inc/docs/core-concepts/test-cases-reimagined/): How Pie generates test cases from natural language prompts with steps and assertions
- [Test Suites](https://docs.pie.inc/docs/core-concepts/test-suites/): Organizing test cases into logical groups for targeted execution
- [Custom Tests](https://docs.pie.inc/docs/core-concepts/custom-tests/): Creating custom test cases with natural language prompts
- [Prompt Best Practices](https://docs.pie.inc/docs/core-concepts/custom-tests/best-practices-prompting/): Writing effective prompts for AI-generated test cases
- [Issues & Findings](https://docs.pie.inc/docs/core-concepts/raw-findings-to-actionable-issues/): How raw test findings are clustered into actionable bug reports
- [Reading Test Reports](https://docs.pie.inc/docs/core-concepts/read-test-issue-reports/): Interpreting test results, visual replays, and issue severity

## Platform Architecture
- [AI Agent Fleet](https://docs.pie.inc/docs/how-it-works/fleet-specialized-ai-modules/): Modular AI architecture with specialized agents for discovery, execution, and analysis
- [End-to-End Testing Flow](https://docs.pie.inc/docs/how-it-works/end-to-end-testing-flow/): How parallel test execution works across the pipeline
- [Self-Healing Tests](https://docs.pie.inc/docs/how-it-works/contextual-understanding-self-healing/): How Pie adapts to UI changes without breaking tests
- [Readiness Score](https://docs.pie.inc/docs/how-it-works/readiness-score-explained/): Quality scoring methodology and how it's calculated

## Testing Capabilities
- [Automated Test Types](https://docs.pie.inc/docs/advanced/): Reference table of 25+ automated test types Pie can execute

## Integrations & CI/CD
- [Available Integrations](https://docs.pie.inc/docs/integrations/available-integrations/): Slack notifications, Jira issue tracking, GitHub Actions, and REST API integration
- [Integration Summary](https://docs.pie.inc/docs/integrations/integration-summary/): Quick reference table of all integrations and their status
- [CI/CD Build Automation](https://docs.pie.inc/docs/integrations/automate-build-uploads/): Automate build uploads via GitHub Actions or REST API
- [iOS Build Preparation](https://docs.pie.inc/docs/integrations/mobile-builds/ios-native/): Preparing native iOS builds (.app files) for testing
- [React Native iOS](https://docs.pie.inc/docs/integrations/mobile-builds/react-native-ios/): Building React Native iOS apps for Pie
- [Android Build Preparation](https://docs.pie.inc/docs/integrations/mobile-builds/android/): Preparing Android APK files for testing
- [Post-Upload Requirements](https://docs.pie.inc/docs/integrations/mobile-builds/post-upload-requirements/): Steps after uploading a build

## Scripts & Data
- [Scripts](https://docs.pie.inc/docs/scripts/): Shell commands (typically curl) that Pie executes during test runs. Reference in test steps with #{script-name} syntax. Use cases: generate unique test data (phone numbers, emails), bypass OTP/KYC/CAPTCHA verification, fetch environment-specific data (payment cards, user profiles), reset test state. Scripts have a 5-minute timeout. Output is captured and available to subsequent test steps.
- [Parameterization](https://docs.pie.inc/docs/scripts/parameterization/): Pass dynamic values between scripts using {{placeholder}} syntax. Chain script outputs - e.g., use a phone number from script 1 as input to script 2's OTP generation.

## Configuration
- [Credential Manager](https://docs.pie.inc/docs/credentials/): Store and manage login credentials for multi-user testing scenarios
- [Bots & Agents](https://docs.pie.inc/docs/bots/): Visual-first agent behavior and operating modes (Observe, Act, Analyze, Handoff)

## Reference
- [Supported Technologies](https://docs.pie.inc/docs/reference/supported-technologies/): Platform and framework compatibility - iOS, Android, Web, React Native, Flutter, and any backend
- [Security & Compliance](https://docs.pie.inc/docs/reference/security-compliance/): SOC 2, GDPR, RBAC, encryption, and data handling policies
- [Glossary](https://docs.pie.inc/docs/reference/glossary-terms/): QA and Pie-specific terminology definitions
- [FAQ](https://docs.pie.inc/docs/faq/): Frequently asked questions