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.
rating : 2.5 points
downloads : 15
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 ManagementIntuitive interface to manage all application and service configurations, supporting real-time status monitoring
Multi-service Type SupportSimultaneously proxy two types of services: SSE (HTTP long connection) and STDIO (command line)
Configuration TemplatingSave commonly used service configurations as templates, supporting JSON import and export for configuration sharing
AI Testing SandboxBuilt-in chat interface to directly test the interaction effects of AI models and tools
Containerized DeploymentProvide Docker support for one-click deployment, ensuring environment consistency
Advantages and Limitations
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 ServiceEncapsulate a third-party weather API as an SSE service for AI Agents to call
Data Analysis ScriptEncapsulate 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
Featured MCP Services

Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
838
4.3 points

Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
151
4.5 points

Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
99
4.3 points

Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
1.7K
5 points

Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
6.7K
4.5 points

Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
573
5 points

Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
5.2K
4.7 points

Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
761
4.8 points