wistx-mcp 1.0.1

WISTX MCP Server - DevOps compliance and pricing context for coding agents

WISTX - MCP Context Server for DevOps

MCP (Model Context Protocol) server providing compliance, pricing, and best practices context for DevOps infrastructure.

🎯 What is WISTX?

WISTX is an MCP server that provides context to LLMs (Claude, GPT-4, etc.) about:

• Compliance Requirements (PCI-DSS, HIPAA, CIS, SOC2, NIST, ISO 27001)
• Infrastructure Pricing (AWS, GCP, Azure)
• Code Examples (Terraform, Kubernetes, Docker)
• Best Practices (DevOps, security, cost optimization)

Users interact with WISTX through:

• MCP Protocol - Native integration with Claude Desktop, Cursor, Windsurf
• REST API - For CI/CD pipelines, scripts, and programmatic access

Features

• 🚀 MCP Server - Native Claude Desktop integration
• 📊 REST API - Simple HTTP endpoints for context retrieval
• 🔍 Vector Search - Semantic search across 50K+ compliance controls
• 💰 Cost Calculator - Real-time infrastructure pricing
• 📝 Code Examples - 500K+ Terraform/K8s examples
• 🔐 API Key Authentication - Secure access control
• 📈 Usage Tracking - Monitor API usage and billing

Requirements

• Python 3.11 or higher
• uv (install with: curl -LsSf https://astral.sh/uv/install.sh | sh)
• MongoDB (for data storage)
• Docker (optional, for containerized deployment)

Installation

Development Setup

1. Clone the repository:

   git clone <repository-url>
   cd wistx-model
   

2. Install uv (if not already installed):

   curl -LsSf https://astral.sh/uv/install.sh | sh
   

3. Copy environment variables:

   cp .env.example .env
   # Edit .env with your configuration
   # IMPORTANT: Add your OpenAI API key for data processing:
   # OPENAI_API_KEY=your-openai-api-key-here
   

4. Install the project and dependencies:

   uv sync
   

5. Run the API server:

   uv run uvicorn api.main:app --reload
   

Architecture

┌─────────────────────────────────────────┐
│  Claude Desktop / Cursor / Windsurf    │
│  (User asks: "Create compliant RDS")    │
└──────────────┬──────────────────────────┘
               │ MCP Protocol
               ↓
┌─────────────────────────────────────────┐
│  WISTX MCP Server                      │
│  ├─ get_compliance_requirements        │
│  ├─ calculate_infrastructure_cost       │
│  ├─ get_code_examples                  │
│  └─ search_best_practices              │
└──────────────┬──────────────────────────┘
               │
               ↓
┌─────────────────────────────────────────┐
│  MongoDB Atlas                          │
│  ├─ compliance_controls (50K+)         │
│  ├─ pricing_data (105K+)               │
│  ├─ code_examples (500K+)               │
│  └─ best_practices (100K+)              │
└─────────────────────────────────────────┘

Project Structure

wistx-model/
├── api/                          # REST API (FastAPI)
│   ├── routers/v1/               # API endpoints
│   │   ├── health.py             # GET /health
│   │   ├── usage.py              # GET /v1/usage
│   │   ├── compliance.py         # GET /v1/compliance (TODO)
│   │   ├── pricing.py            # GET /v1/pricing (TODO)
│   │   └── code.py               # GET /v1/code-examples (TODO)
│   ├── middleware/               # API middleware
│   │   ├── auth.py               # API key authentication
│   │   ├── rate_limit.py         # Rate limiting
│   │   └── logging.py            # Request logging
│   ├── services/                 # Business logic
│   │   ├── billing_service.py   # Billing logic
│   │   ├── usage_tracker.py      # Usage tracking
│   │   └── token_counter.py      # Token counting
│   ├── database/                 # MongoDB connection
│   └── auth/                     # Authentication
│
├── wistx_mcp/                    # MCP Server (TODO - Week 5)
│   ├── server.py                 # MCP server main
│   └── tools/                    # MCP tools
│       ├── compliance.py         # Compliance context
│       ├── pricing.py            # Pricing context
│       ├── code_examples.py      # Code examples
│       └── lib/                  # Shared utilities
│           ├── mongodb_client.py # MongoDB queries
│           ├── vector_search.py  # Vector search
│           └── context_builder.py # Context formatting
│
├── data-pipelines/               # Data collection & processing
│   ├── collectors/               # Data collectors
│   ├── processors/               # Data processors
│   ├── loaders/                  # MongoDB loaders
│   └── models/                   # Data models
│
├── scripts/                       # Utility scripts
│   ├── setup_mongodb.py          # MongoDB setup
│   ├── run_compliance_collection.py  # Data collection
│   └── validate_mongodb_complete.py  # Validation
│
├── tests/                        # Test suite
├── pyproject.toml                # Project configuration
├── docker-compose.yml            # Docker Compose setup
└── README.md

Data Processing Pipeline

The data processing pipeline collects, processes, embeds, and loads compliance data into MongoDB and Pinecone.

Prerequisites

1. Environment Variables - Ensure your .env file includes:

   # Required for data processing
   OPENAI_API_KEY=your-openai-api-key-here
   MONGODB_URL=mongodb://localhost:27017
   MONGODB_DATABASE=wistx-production
   PINECONE_API_KEY=your-pinecone-api-key
   PINECONE_INDEX_NAME=wistx-index
   

2. MongoDB Setup - Initialize MongoDB collections and indexes:

   python scripts/setup_mongodb.py
   

3. Dependencies - Install required packages:

   uv sync
   # Optional: For PDF processing
   uv add docling
   

Running the Pipeline

Process a single compliance standard (full pipeline):

python scripts/run_pipeline.py --standard PCI-DSS --mode streaming

Process all compliance standards:

python scripts/run_pipeline.py --mode streaming

Skip collection stage (use existing raw data):

python scripts/run_pipeline.py --standard PCI-DSS --mode streaming --no-collection

Development mode (saves intermediate files for debugging):

python scripts/run_pipeline.py --standard PCI-DSS --mode checkpointing

Pipeline Modes

• Streaming Mode (--mode streaming): Production mode - no intermediate files saved, faster execution
• Checkpointing Mode (--mode checkpointing): Development mode - saves intermediate files at each stage for debugging and resuming

Available Standards

• PCI-DSS, CIS, HIPAA, SOC2, NIST-800-53, ISO-27001, GDPR, FedRAMP, CCPA, SOX, GLBA

Pipeline Stages

1. Collection - Scrapes URLs/web pages (Crawl4AI) and processes PDFs (Docling)
2. Processing - Standardizes raw data into ComplianceControl models
3. Embedding - Generates vector embeddings using OpenAI API
4. Loading - Stores documents in MongoDB and vectors in Pinecone

For detailed pipeline documentation, see data-pipelines/HOW_TO_RUN_PIPELINE.md

Development

Running Tests

# Run all tests
uv run pytest

# Run with coverage
uv run pytest --cov

# Run specific test file
uv run pytest tests/api/test_messages.py

Code Quality

# Format code with black
uv run black .

# Lint with ruff
uv run ruff check .

# Type check with mypy
uv run mypy .

Adding Dependencies

# Add a runtime dependency
uv add <package-name>

# Add a development dependency
uv add --group dev <package-name>

Docker Deployment

# Start all services
docker-compose up -d

# View logs
docker-compose logs -f

# Stop services
docker-compose down

API Endpoints

Current

• GET /health - Health check
• GET /v1/usage - Get usage statistics

Planned (Week 6)

• GET /v1/compliance - Get compliance requirements
• GET /v1/pricing - Calculate infrastructure costs
• GET /v1/code-examples - Search code examples
• GET /v1/best-practices - Search best practices

OpenAPI Specification

The REST API exposes an OpenAPI specification:

• OpenAPI spec: http://localhost:8000/openapi.json
• Interactive docs: http://localhost:8000/docs

SDKs can be generated from the OpenAPI spec using openapi-generator if needed.

The MCP server provides these tools:

• get_compliance_requirements - Get compliance controls for resources
• calculate_infrastructure_cost - Calculate costs for infrastructure
• get_code_examples - Get relevant code examples
• search_best_practices - Search DevOps best practices
• check_compliance_violations - Check code for compliance issues
• suggest_cost_optimizations - Suggest cost savings

Documentation

• MCP Architecture Guide - Complete MCP implementation guide
• MongoDB Setup - MongoDB configuration and schema
• Data Pipeline - Data collection and processing
• Architecture Review - Migration details

License

MIT License

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.