workflow-integration.md•10.2 kB
# MCP Titan Workflow Integration Guide
## Overview
This document describes the complete workflow integration for the MCP Titan tool, enabling seamless integration into any AI agent system for automated software development lifecycle management.
## Core Workflow Components
### 1. Automatic Release PR Creation
#### Release Detection
```typescript
interface ReleaseConfig {
versionBump: "patch" | "minor" | "major";
triggerConditions: {
commitCount: number;
timeThreshold: string; // e.g., '7d', '14d'
featureFlags: string[];
};
channels: {
stable: string;
beta: string;
alpha: string;
};
}
```
#### Workflow Triggers
- **Commit-based**: Automatically trigger after N commits to main
- **Time-based**: Weekly/monthly release cycles
- **Feature-based**: When specific feature flags are completed
- **Manual**: Via agent command or GitHub webhook
#### PR Creation Process
1. **Version Analysis**: Analyze commits since last release using conventional commits
2. **Changelog Generation**: Auto-generate changelog from commit messages
3. **Dependency Updates**: Check for security updates and compatible version bumps
4. **Test Suite Execution**: Run full test suite before PR creation
5. **PR Template Population**: Use intelligent templates based on change type
```typescript
interface ReleasePR {
title: string;
body: string;
labels: string[];
assignees: string[];
reviewers: string[];
milestone?: string;
metadata: {
changeType: "breaking" | "feature" | "fix" | "docs";
affectedComponents: string[];
testCoverage: number;
performanceImpact?: string;
};
}
```
### 2. GitHub Issue Management
#### Issue Classification System
```typescript
interface IssueClassification {
type: "bug" | "feature" | "enhancement" | "question" | "documentation";
priority: "critical" | "high" | "medium" | "low";
complexity: "trivial" | "simple" | "moderate" | "complex";
component: string[];
estimatedHours?: number;
dependencies?: string[];
}
```
#### Automatic Issue Processing
1. **Content Analysis**: Use NLP to understand issue context
2. **Duplicate Detection**: Check against existing issues using similarity matching
3. **Auto-labeling**: Apply relevant labels based on content analysis
4. **Assignment Logic**: Route to appropriate team members
5. **Template Validation**: Ensure issues follow required format
#### Issue Resolution Workflow
```typescript
interface IssueResolution {
analysisPhase: {
rootCauseAnalysis: boolean;
reproductionSteps: string[];
affectedVersions: string[];
};
implementationPhase: {
branchCreated: boolean;
testsWritten: boolean;
codeReviewed: boolean;
};
validationPhase: {
manualTesting: boolean;
automatedTesting: boolean;
performanceTesting: boolean;
};
}
```
### 3. Feedback Collection and Processing
#### Multi-channel Feedback Integration
```typescript
interface FeedbackChannels {
github: {
issues: boolean;
discussions: boolean;
pullRequests: boolean;
};
external: {
slack: boolean;
discord: boolean;
email: boolean;
surveys: boolean;
};
analytics: {
errorTracking: boolean;
usageMetrics: boolean;
performanceMetrics: boolean;
};
}
```
#### Feedback Processing Pipeline
1. **Collection**: Aggregate feedback from all configured channels
2. **Sentiment Analysis**: Classify feedback as positive/negative/neutral
3. **Topic Modeling**: Extract key themes and topics
4. **Prioritization**: Score feedback based on impact and frequency
5. **Action Generation**: Create actionable items from feedback
```typescript
interface FeedbackItem {
id: string;
source: string;
timestamp: Date;
content: string;
sentiment: "positive" | "negative" | "neutral";
topics: string[];
priority: number;
actionItems: string[];
metadata: Record<string, any>;
}
```
### 4. Intelligent Labeling System
#### Label Taxonomy
```typescript
interface LabelTaxonomy {
type: {
bug: "#d73a49";
feature: "#0075ca";
enhancement: "#a2eeef";
documentation: "#0052cc";
question: "#d876e3";
};
priority: {
"priority: critical": "#b60205";
"priority: high": "#d93f0b";
"priority: medium": "#fbca04";
"priority: low": "#0e8a16";
};
component: {
"component: core": "#1d76db";
"component: api": "#5319e7";
"component: ui": "#f9d0c4";
"component: docs": "#c2e0c6";
};
status: {
"status: triage": "#fbca04";
"status: in-progress": "#0052cc";
"status: blocked": "#d73a49";
"status: ready-for-review": "#0075ca";
};
}
```
#### Auto-labeling Rules
```typescript
interface LabelingRules {
textPatterns: {
pattern: RegExp;
labels: string[];
confidence: number;
}[];
filePatterns: {
pattern: string;
labels: string[];
}[];
userRoles: {
role: string;
defaultLabels: string[];
}[];
contextual: {
condition: string;
labels: string[];
}[];
}
```
### 5. Linting and Code Quality
#### Multi-level Linting Strategy
```typescript
interface LintingConfig {
levels: {
syntax: {
enabled: boolean;
tools: string[];
failOnError: boolean;
};
style: {
enabled: boolean;
config: string;
autoFix: boolean;
};
security: {
enabled: boolean;
tools: string[];
severity: "error" | "warning";
};
performance: {
enabled: boolean;
thresholds: Record<string, number>;
};
};
integrations: {
preCommit: boolean;
prChecks: boolean;
cicd: boolean;
};
}
```
#### Quality Gates
```typescript
interface QualityGates {
coverage: {
minimum: number;
delta: number;
};
complexity: {
cyclomatic: number;
cognitive: number;
};
duplication: {
percentage: number;
};
security: {
vulnerabilities: number;
licenses: string[];
};
}
```
## Agent Integration Points
### 1. Memory-Enhanced Decision Making
The MCP Titan tool maintains context across interactions to improve decision quality:
```typescript
interface AgentMemory {
projectContext: {
codebase: string;
architecture: string;
conventions: Record<string, any>;
};
workflowHistory: {
successfulPatterns: Pattern[];
failedAttempts: FailureAnalysis[];
userPreferences: UserPreferences;
};
learningMetrics: {
accuracyScore: number;
adaptationRate: number;
contextRetention: number;
};
}
```
### 2. Workflow Orchestration
```typescript
interface WorkflowOrchestrator {
triggers: {
webhooks: WebhookConfig[];
schedules: ScheduleConfig[];
manual: ManualTriggerConfig[];
};
pipelines: {
parallel: Pipeline[];
sequential: Pipeline[];
conditional: ConditionalPipeline[];
};
monitoring: {
healthChecks: HealthCheck[];
metrics: MetricConfig[];
alerts: AlertConfig[];
};
}
```
### 3. Integration APIs
#### GitHub Integration
```typescript
interface GitHubIntegration {
authentication: {
token: string;
app: GitHubApp;
};
permissions: {
repositories: string[];
scopes: string[];
};
webhooks: {
events: string[];
secret: string;
url: string;
};
}
```
#### Notification Systems
```typescript
interface NotificationSystem {
channels: {
slack: SlackConfig;
email: EmailConfig;
webhook: WebhookConfig;
};
templates: {
success: string;
failure: string;
warning: string;
};
routing: {
rules: RoutingRule[];
fallback: string;
};
}
```
## Implementation Strategy
### Phase 1: Core Workflow Components (Week 1)
1. Set up GitHub API integration
2. Implement basic issue classification
3. Create release PR automation
4. Add fundamental linting pipeline
### Phase 2: Intelligence Layer (Week 2)
1. Integrate MCP Titan memory system
2. Add sentiment analysis for feedback
3. Implement smart labeling rules
4. Create learning feedback loops
### Phase 3: Advanced Features (Week 3)
1. Multi-channel feedback integration
2. Advanced quality gates
3. Performance monitoring
4. Predictive analytics
### Phase 4: Optimization (Week 4)
1. Performance tuning
2. Error handling improvements
3. User experience enhancements
4. Documentation and testing
## Configuration Schema
```typescript
interface WorkflowConfig {
repository: {
owner: string;
name: string;
branch: string;
};
features: {
autoRelease: ReleaseConfig;
issueManagement: IssueConfig;
feedback: FeedbackConfig;
labeling: LabelConfig;
linting: LintConfig;
};
integrations: {
github: GitHubIntegration;
notifications: NotificationSystem;
analytics: AnalyticsConfig;
};
memory: {
titanConfig: TitanMemoryConfig;
persistence: PersistenceConfig;
};
}
```
## Success Metrics
### Automation Metrics
- **Release Frequency**: Target 2x increase in release cadence
- **Issue Resolution Time**: Target 50% reduction in average resolution time
- **Code Quality**: Maintain >95% quality gate pass rate
- **Feedback Response**: Target <24h response time to feedback
### Learning Metrics
- **Memory Retention**: >90% context accuracy across sessions
- **Prediction Accuracy**: >85% accuracy in workflow predictions
- **Adaptation Rate**: <1 week to adapt to new patterns
- **User Satisfaction**: >4.5/5 in agent interaction quality
## Error Handling and Recovery
### Failure Modes
1. **API Rate Limits**: Exponential backoff with jitter
2. **Network Issues**: Circuit breaker pattern with retries
3. **Memory Corruption**: Automatic checkpoint recovery
4. **Permission Errors**: Graceful degradation with notifications
### Recovery Strategies
```typescript
interface RecoveryStrategy {
detection: {
healthChecks: HealthCheck[];
anomalyDetection: boolean;
};
response: {
automated: AutomatedResponse[];
manual: ManualIntervention[];
};
prevention: {
proactiveMonitoring: boolean;
predictiveAnalysis: boolean;
};
}
```
This workflow integration provides a comprehensive framework for any agent to leverage the MCP Titan tool for complete software development lifecycle automation while maintaining memory and learning capabilities across interactions.