Catalyst MCP Server
Provides tools for repository management, CI/CD, code management, and deployment tracking.
Enables GitLab API integration for project management and pipeline monitoring.
Integrates with Google Gemini AI models for AI capabilities.
Offers server management and monitoring, including system administration and log analysis.
Integrates with OpenAI GPT models for AI-powered interactions.
Allows database queries and reporting for business intelligence and data analysis.
Supports message queue management, monitoring, and handling.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Catalyst MCP Serverget latest orders from PostgreSQL Analytics"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Catalyst MCP Server
MCP (Model Context Protocol) server implementation that loads and serves Knowledge Packs.
Features
MCP server implementation with FastAPI
LibreChat integration for web interface
Docker deployment support
Knowledge Pack loading from YAML configurations
Authentication and rate limiting
Support for multiple AI models (Claude, GPT, Gemini)
Quick Start
1. Clone and Configure
# Clone the repository
git clone https://github.com/billebel/catalyst_mcp.git
cd catalyst_mcp
# Copy environment template
cp .env.example .env
# Edit .env with your API keys
nano .env2. Set Your API Keys
Edit .env file:
# Add your API keys
ANTHROPIC_API_KEY=your-claude-api-key
OPENAI_API_KEY=your-openai-api-key # Optional
GOOGLE_API_KEY=your-gemini-api-key # Optional
# JWT secrets (change for production!)
JWT_SECRET=your-secure-jwt-secret
JWT_REFRESH_SECRET=your-secure-refresh-secret3. Start with Docker
# Start the complete stack
docker-compose up -d
# View logs
docker-compose logs -f4. Access Your AI Assistant
Web Chat Interface: http://localhost:3080
MCP Server: http://localhost:8443
API Documentation: http://localhost:8443/docs
Architecture
graph TD
A[AI Assistant<br/>Claude Desktop] --> B[MCP Protocol]
C[Web Chat<br/>LibreChat] --> B
B --> D[Catalyst MCP Server]
D --> E[Knowledge Packs]
E --> F[Your Business Systems]
F --> G[Databases]
F --> H[REST APIs]
F --> I[Cloud Services]Knowledge Packs
Catalyst includes example Knowledge Packs for common business systems:
Pack | Description | Use Cases |
PostgreSQL Analytics | Database queries and reporting | Business intelligence, data analysis |
GitHub DevOps | Repository management and CI/CD | Code management, deployment tracking |
GitLab DevOps | GitLab API integration | Project management, pipeline monitoring |
Linux Server Admin | Server management and monitoring | System administration, log analysis |
RabbitMQ Messaging | Message queue management | Queue monitoring, message handling |
S3 Storage | AWS S3 file operations | File management, backup operations |
Creating Custom Packs
Create Knowledge Packs using the Catalyst Builder:
# Install the pack builder
pip install catalyst-builder
# Create a new CRM integration pack
catalyst-packs create crm-integration \
--type rest \
--description "Connect to our CRM system"
# This generates a complete pack structure:
# crm-integration/
# ├── pack.yaml # Main configuration
# ├── tools/ # Tool definitions
# ├── prompts/ # AI prompts
# └── README.md # DocumentationThe generated pack.yaml:
metadata:
name: crm-integration
description: "Connect to our CRM system"
domain: sales
connection:
type: rest
base_url: "https://api.yourcrm.com/v1"
auth:
method: bearer
token: "${CRM_API_TOKEN}"
tools:
- name: search_customers
type: search
description: "Find customers by name or email"
endpoint: "/customers/search"Pack Builder Resources:
Catalyst Builder GitHub - Complete documentation
Getting Started Guide - Step-by-step tutorial
CLI Reference - All available commands
Pack Development Guide - Advanced configuration
Deployment Options
Docker Compose (Recommended)
# Production deployment
docker-compose up -d
# Development with hot reload
docker-compose -f docker-compose.yml -f docker-compose.override.yml up -dLocal Development
# Install Python dependencies
pip install -r requirements.txt
# Start MCP server
python -m catalyst_mcp.server
# Start chat interface (separate terminal)
# See docs/chat-customization.md for LibreChat setupConfiguration
Environment Variables
Variable | Description | Required | Default |
| MCP server port | No |
|
| Server bind address | No |
|
| Logging level | No |
|
| Claude API key | Yes* | - |
| OpenAI API key | No | - |
| Gemini API key | No | - |
| Chat authentication | Yes | - |
| Allow new users | No |
|
*At least one AI provider API key is required.
Chat Interface Customization
Catalyst uses LibreChat for the web interface. Customize:
Branding: Edit
librechat.yamlfor colors, logosAuthentication: Configure OAuth providers in
.envModels: Enable/disable AI models per user
Plugins: Add custom plugins and tools
AI Assistant Integration
Claude Desktop
Add to your Claude Desktop configuration:
{
"mcpServers": {
"catalyst": {
"command": "mcp-client",
"args": ["--url", "http://localhost:8443"]
}
}
}ChatGPT/OpenAI
Use the MCP-compatible plugin or direct API integration.
Custom AI Applications
Connect any MCP-compatible AI application:
import mcp_client
# Connect to Catalyst MCP server
client = mcp_client.MCPClient("http://localhost:8443")
# Use business tools
result = client.call_tool("search_customers", {"query": "ACME Corp"})Security Features
Authentication & Authorization
JWT-based session management
Role-based access control
OAuth provider integration (GitHub, Google, etc.)
API Security
Rate limiting and request throttling
Input validation and sanitization
Audit logging for compliance
Deployment Security
HTTPS/TLS encryption
Environment variable secrets
Container isolation
Examples & Use Cases
Business Intelligence
Use the Catalyst Builder to create database analytics packs:
catalyst-packs create bi-dashboard --type database --description "Executive dashboard"DevOps Automation
Create deployment and monitoring packs:
catalyst-packs create devops-tools --type rest --description "CI/CD automation"Customer Support
Build support system integrations:
catalyst-packs create support-tools --type rest --description "Help desk integration"Community & Support
Catalyst Builder: catalyst-builder on PyPI
Documentation: Complete Pack Development Guide
GitHub Issues: Report bugs and request features
License
MIT License
Quick Commands
# Start everything
docker-compose up -d
# View logs
docker-compose logs -f catalyst-mcp
# Stop services
docker-compose down
# Create custom packs
pip install catalyst-builder
catalyst-packs create my-integration --type restGetting Started
Clone repository:
git clone https://github.com/billebel/catalyst_mcp.gitInstall pack builder:
pip install catalyst-builderCreate packs as needed
Deploy with Docker:
docker-compose up -d
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