# Success Metrics

## MVP Success Criteria (Phase 1 - Specs 001-008)

**Operational Success**:
- **<100ms semantic search latency**: Natural language queries ("slow queues") return relevant operations within 100ms
- **<200ms operation execution**: Basic operations (list queues, create exchange) complete in under 200ms
- **Zero credential leaks**: Automated security scanning finds no passwords/tokens in logs or error messages
- **80%+ test coverage**: All critical paths (connections, operations, safety validations) covered by tests
- **100% MCP protocol compliance**: Passes all MCP specification validation tests

**User Adoption Metrics** (Post-Launch):
- **50+ GitHub stars** in first 3 months (developer interest indicator)
- **10+ production deployments** within 6 months (enterprise adoption)
- **5+ community contributions** (PRs, issues, documentation improvements)
- **90% operation success rate**: Operations complete successfully without errors

**Developer Experience Metrics**:
- **<5 minutes first operation**: From `uvx rabbitmq-mcp-server` to executing first operation
- **<30 minutes onboarding**: New developers comfortable with all 3 tools (search, get, call)
- **Zero API documentation lookups**: Developers rely on semantic search, not external docs

## Business Objectives

**Primary Objective**: Establish RabbitMQ MCP Server as the **standard tool** for AI-assisted RabbitMQ management in the Python ecosystem.

**Secondary Objectives**:
- Reduce DevOps/SRE time spent on RabbitMQ operations by 50% (measured via user surveys)
- Demonstrate OpenAPI-driven MCP server pattern for the ecosystem
- Build community around AI-assisted infrastructure management
- Enable enterprise adoption with production-ready quality (security, observability, compliance)

**Long-Term Vision** (Phase 2 - Specs 009-020):
- Support for advanced RabbitMQ features (plugins, clustering, federation)
- Enterprise log aggregation integrations (ELK, Splunk, CloudWatch)
- Multi-language support (internationalization)
- Advanced monitoring and performance optimization
- Become reference architecture for API-to-MCP transformations

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