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MCPO Project
This repository contains the source code, configuration files, and deployment instructions for a project that uses Docker, Kubernetes, and the mcpo
tool to manage mulitiple MCP (Multi-Component Protocol) service.
Overview
The project sets up:
- A Docker container running the
mcpo
tool with configuration frommcpo_config.json
- A Kubernetes deployment for the Gitea MCP application
- Services and pods to manage the application's networking and lifecycle
Key Components
Docker
- Dockerfile: Builds a container with Python dependencies and the
mcpo
tool - gitea_mcp_set.sh: Script to configure gitea_mcp in the container environment
- requirements.txt: Python dependencies for any script-based components
Kubernetes
- kube/deployment.yaml: Defines the Kubernetes deployment for the Gitea MCP application
- kube/pod.yaml: Pod specification for the container
- kube/service.yaml: Service configuration to expose the application
Configuration
- mcpo_config.json: Main configuration file for the
mcpo
tool, containing:- MCP server settings
- Authentication credentials
- API endpoints
Purpose
This project provides a complete environment to:
- Run the mpco service using containerization
- Orchestrate the service using Kubernetes
- Manage configuration and authentication securely
Setup Instructions
-
Clone the repository:
git clone [repository-url]
-
Build the Docker image:
docker build -t gitea-mcp:latest .
-
Apply Kubernetes configurations:
kubectl apply -f kube/
-
Verify the deployment:
kubectl get pods -n gitea-mcp kubectl get services -n gitea-mcp
-
Test the service:
- Ensure the service is accessible through the NodePort (30026)
- Verify the MCP servers are configured correctly
Notes
- The
mcpo
tool is used to manage MCP connections - The configuration file contains sensitive information (access tokens, Bearer tokens)
- The project is designed for production deployment with Kubernetes orchestration
For detailed explanations of individual components, refer to their respective files in the repository.
Description
Languages
Python
64.2%
Dockerfile
22%
Shell
13.8%