Mcpez
MCPez is a microservice command proxy management platform that unifies the management and standardizes the backend service interfaces through a web interface, simplifying the integration and deployment of applications such as AI agents.
2.5 points
8.2K

What is MCPez?

MCPez is a microservice command proxy management platform that helps users easily manage various backend services (such as AI models, local scripts, or remote APIs) through a web interface. It encapsulates different services into standard interfaces, solving the fragmentation problem in the microservice ecosystem.

How to use MCPez?

After one-click deployment via Docker, create an application on the web interface and add service configurations (SSE or STDIO types). Then, you can call these services through the unified proxy address. Clients such as AI Agents only need to interact with the proxy interface without caring about the underlying implementation details.

Applicable Scenarios

Suitable for AI Agent development that needs to integrate multiple tools/services, enterprise internal service governance, and developers who want to avoid being locked in by a single platform. Especially applicable to scenarios where multiple microservices need to be combined to build complex applications.

Main Features

Visual Web Management
Intuitive interface to manage all application and service configurations, supporting real-time status monitoring
Multi-service Type Support
Simultaneously proxy two types of services: SSE (HTTP long connection) and STDIO (command line)
Configuration Templating
Save commonly used service configurations as templates, supporting JSON import and export for configuration sharing
AI Testing Sandbox
Built-in chat interface to directly test the interaction effects of AI models and tools
Containerized Deployment
Provide Docker support for one-click deployment, ensuring environment consistency
Advantages
Break service silos: Unified management of scattered microservices
Reduce integration costs: Clients only need to connect to standardized interfaces
Configuration flexibility: Support custom parameters such as Headers/environment variables
Localized security: Sensitive information is not uploaded to third-party platforms
Ecological openness: Avoid being locked in by specific service providers
Limitations
Basic Docker knowledge is required for deployment
SSE services require backend support for the long connection protocol
Currently only supports single-machine deployment, lacking a cluster solution

How to Use

Deploy the Platform
Start the container service through Docker commands
Create an Application
Click 'New Service' on the web interface and fill in the application name and description
Add Service Configuration
Add SSE or STDIO type service configurations for the application and fill in the necessary parameters
Start the Service
For STDIO services, click the start button on the home page; SSE services take effect automatically
Call the Service
Access the service through the returned proxy address (e.g., /mcp/<app_id>/sse)

Usage Examples

Weather Query Service
Encapsulate a third-party weather API as an SSE service for AI Agents to call
Data Analysis Script
Encapsulate a local Python data analysis script as an STDIO service

Frequently Asked Questions

What's the difference between SSE and STDIO services?
How to view service logs?
Do I need to restart after modifying the configuration?

Related Resources

GitHub Repository
Project source code and latest version
Docker Documentation
Docker installation and usage guide
SSE Protocol Description
Server-Sent Events technical specification

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

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