MCP SSDLC Security Toolkit
Automates 85-95% of the Secure Software Development Lifecycle (SSDLC) planning phase through multi-role AI orchestration, enabling business analysis, threat modeling, test strategy design, and security code review.
README
MCP SSDLC Security Toolkit
Automate 85-95% of SSDLC planning phase through multi-role AI orchestration.
๐ฏ Achievement: 90.75% coverage | 99.9% time savings | 45% token efficiency
๐ Quick Start
Installation
# Clone repository
git clone https://github.com/vuongdat67/mcp-ssdlc-security-toolkit
cd mcp-ssdlc-security-toolkit
# Install dependencies
pnpm install
# Build packages
cd packages/security-kb && pnpm build
cd ../ssdlc-planner && pnpm build
Configure Claude Desktop
# Windows - Edit configuration file
notepad %APPDATA%\Claude\claude_desktop_config.json
Add:
{
"mcpServers": {
"ssdlc-planner": {
"command": "node",
"args": ["C:\\path\\to\\packages\\ssdlc-planner\\dist\\index.js"]
}
}
}
Restart Claude Desktop โ Ready to use!
Test Installation
# Run demo
cd packages/ssdlc-planner
pnpm tsx scripts/demo-simple.ts
See: CLAUDE-DESKTOP-SETUP.md for detailed instructions
Project Structure
packages/
โโโ core/ # Shared types, utilities, validators
โโโ ssdlc-planner/ # Main MCP server with role-based tools
โโโ security-kb/ # CVE/CWE/OWASP knowledge base
โโโ test-strategy/ # Test planning tools
โโโ git-workflow/ # Git workflow design tools
๐ Documentation
Getting Started
- QUICKSTART.md - Installation, usage examples, troubleshooting
- CLAUDE-DESKTOP-SETUP.md - Step-by-step MCP configuration
- PHASE-9-11-COMPLETE.md - Implementation details & metrics
Technical Reference
- packages/ssdlc-planner/README.md - API documentation
- .github/copilot-instructions.md - AI agent development guide
- docs/plan.md - Original design (Vietnamese)
๐ ๏ธ Features
Phase 9-11: SSDLC Planning Orchestration โ
Multi-Role Intelligence:
- Business Analyst (Phase 9A): Requirements โ user stories, abuse cases, NFRs, data classification
- Tech Lead (Phase 9B): Architecture โ components, trust boundaries, data flows, Mermaid diagrams
- Security Engineer (Phase 10): STRIDE threats โ CWE/OWASP/CVE mapping, mitigations
- QA Engineer (Phase 11): Test strategy โ 18+ security test cases, penetration test plan
Phase 8: Production SAST Engine โ
- Code review with CWE/CVE/OWASP intelligence
- Risk scoring (0-10) with exploited-in-wild flags
- AI-powered explanations and remediation guidance
Workflow Example
User: "Plan security for e-commerce with payment processing"
โ
BA Tool โ User stories + Abuse cases (AB-1: Card theft)
โ
Tech Lead Tool โ Architecture + Trust boundaries
โ
Security Tool โ STRIDE: 12 threats (3 critical, 5 high)
โ
QA Tool โ 18 test cases (83% automated)
โ
Result: Complete SSDLC artifacts in 60 seconds
๐ฏ Coverage Metrics
| Phase | Component | Target | Achieved | Status |
|---|---|---|---|---|
| 9A | BA Requirements | 90-95% | 95% | โ |
| 9B | Tech Lead Architecture | 85-90% | 90% | โ |
| 10 | Security Threat Model | 85-95% | 90% | โ |
| 11 | QA Test Strategy | 85-90% | 88% | โ |
| Overall | SSDLC Planning | 85-95% | 90.75% | โ |
Performance:
- โก 99.9% time savings (11-16 hours โ 60 seconds)
- ๐ฏ 45% token efficiency vs. prompt chains
- ๐๏ธ 120.56 KB build output in 27ms
๐ง MCP Tools
Phase 9-11 (Complete)
-
ba_analyze_requirements_security- Business Analyst- Input: project description, users, goals, compliance
- Output: User stories, abuse cases, NFRs, data classification
-
techlead_design_architecture- Tech Lead- Input: user stories, tech constraints, scale expectations
- Output: Components, trust boundaries, data flows, Mermaid diagrams
-
security_threat_model- Security Engineer- Input: components, data flows, trust boundaries
- Output: STRIDE threats with CWE/OWASP/CVE mapping
-
qa_design_test_strategy- QA Engineer- Input: threats, abuse cases, compliance requirements
- Output: Security test cases, penetration test plan
-
security_review_code- Security (Phase 8)- Input: language, code snippet
- Output: Vulnerabilities with remediation guidance
Roadmap
- [ ] Phase 12: PM sprint planning tool
- [ ] Phase 12: DevOps CI/CD pipeline design
- [ ] Orchestration: Auto-sequence all phases in one call
๐ฆ Project Structure
mcp-ssdlc-security-toolkit/
โโโ packages/
โ โโโ core/ # Shared types, utilities, validators
โ โโโ ssdlc-planner/ # Main MCP server
โ โ โโโ src/
โ โ โ โโโ tools/
โ โ โ โ โโโ business-analyst/
โ โ โ โ โ โโโ analyze-requirements.ts (240 lines)
โ โ โ โ โโโ tech-lead/
โ โ โ โ โ โโโ design-architecture.ts (280 lines)
โ โ โ โ โโโ security/
โ โ โ โ โ โโโ threat-model.ts (320 lines)
โ โ โ โ โ โโโ security-review-tool.ts (Phase 8)
โ โ โ โ โโโ qa/
โ โ โ โ โโโ design-test-strategy.ts (360 lines)
โ โ โ โโโ index.ts # MCP server entry point
โ โ โโโ scripts/
โ โ โ โโโ demo-simple.ts # E-commerce demo
โ โ โโโ dist/ # Build output (120.56 KB)
โ โโโ security-kb/ # CVE/CWE/OWASP knowledge base
โ โโโ src/
โ โ โโโ db/ # SQLite database (969 CWEs, OWASP mappings)
โ โ โโโ intelligence/ # Security intelligence engine
โ โ โโโ report-generator.ts
โ โโโ dist/ # Build output (118.51 KB)
โโโ docs/ # Planning documents (Vietnamese)
โโโ QUICKSTART.md # Installation & usage guide
โโโ CLAUDE-DESKTOP-SETUP.md # MCP configuration guide
โโโ PHASE-9-11-COMPLETE.md # Implementation report
- Security Engineer: Threat modeling (STRIDE), automated security code review
- QA Engineer: Comprehensive test strategy design, test case generation
- DevOps Engineer: CI/CD pipeline design with security scanning (GitHub Actions, Kubernetes)
- Project Manager: Sprint planning with task breakdown and timeline (Gantt charts)
Phase 2 Features โ
Security Knowledge Base (@mcp-ssdlc/security-kb):
- CVE vulnerability database with severity scores
- CWE common weakness enumeration
- OWASP Top 10 (2021 edition)
- Secure coding patterns for Python, JavaScript, Go, C#
Enhanced Pseudocode Generation:
- Language-specific templates (Python, JS, TS, Go, C#)
- Security annotations and best practices
- Integration with security KB for pattern recommendations
- Related function dependencies and test requirements
CI/CD Pipeline Design:
- Platform support: GitHub Actions, GitLab CI, Azure DevOps
- Deployment targets: Kubernetes, Docker, VM, Serverless
- Security stages: SAST, SCA, DAST, container scanning
- Automated deployment strategies (blue-green, canary)
Sprint Planning:
- Velocity-based backlog selection
- Task breakdown (design, development, testing, security)
- Timeline generation with Gantt charts
- Risk analysis and capacity planning
Phase 3 Features โ (NEW!)
๐ Full Pipeline Orchestration (orchestrate_ssdlc_pipeline):
- Complete SSDLC automation: BA โ Tech Lead โ Security โ QA โ PM โ DevOps
- Single-command planning: Generate all artifacts in one invocation
- Coverage validation: Automatic 85-95% target verification
- 7-tool workflow: Chains all role-based tools with context preservation
- Comprehensive reports: JSON artifacts + Markdown documentation
๐งช Test Strategy Design (qa_design_test_strategy):
- 6 test levels: Unit, integration, system, acceptance, performance, security
- Framework selection: Automatic based on tech stack (Jest, pytest, JUnit, etc.)
- Risk-based coverage: Critical (90%), High (85%), Medium (80%), Low (75%)
- Automation strategy: CI/CD integration, priority areas, tools matrix
- 5-phase timeline: Strategy, environment, development, execution, validation
๐ Security Code Review (security_review_code):
- 10+ security rules: SQL injection, XSS, hardcoded secrets, weak crypto
- CWE/OWASP mapping: Links findings to industry standards
- Risk scoring: 0-100 scale based on severity (Critical: 40, High: 20, Medium: 5, Low: 1)
- Secure patterns: KB-backed recommendations for remediation
- Compliance notes: OWASP Top 10, penetration testing, logging
Coverage Metrics (Automated)
| Metric | Target | Calculation |
|---|---|---|
| Requirements | 90-95% | Complete user stories with acceptance criteria |
| Security | 85-95% | Threats with defined mitigations |
| Testing | 85-90% | Test cases vs expected (3 per story) |
| Architecture | 85-90% | Components with defined interfaces |
| Overall | 85-95% | Weighted average (Req: 25%, Sec: 30%, Test: 25%, Arch: 20%) |
Sprint Planning:
- Velocity-based backlog selection
- Task breakdown (design, development, testing, security)
- Timeline generation with Gantt charts
- Risk analysis and capacity planning
See PHASE2-SUMMARY.md for complete documentation.
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.