This repository offers MCP server implementations across multiple languages, facilitating AI communication with tools through a consistent protocol, primarily for VS Code integration.
This repository offers MCP server implementations across multiple languages, facilitating AI communication with tools through a consistent protocol, primarily for VS Code integration.
The MCP servers implement the Model Context Protocol, allowing AI agents to interact seamlessly with various tools and services. The Python server is fully operational, supporting comprehensive features like SSE, JSON-RPC, error handling, and monitoring. The Go and Rust servers are in progress, aiming to provide core MCP functionalities and integration capabilities. These servers enable real-time data exchange, diagnostics, and enhanced developer support in AI toolchains, ensuring standardized communication between AI and external systems.
Who will use Model Context Protocol (MCP) Servers?
AI developers
Tool integrators
VS Code users
AI research teams
How to use the Model Context Protocol (MCP) Servers?
Step1: Install Docker and Docker Compose
Step2: Clone the repository from GitHub
Step3: Run 'docker-compose up' to start servers
Step4: Configure your IDE (e.g., VS Code) to connect to the server endpoint
Step5: Use the MCP protocol features via supported tools
Model Context Protocol (MCP) Servers's Core Features & Benefits
The Core Features
Supports MCP protocol in Python, Go, and Rust
Provides endpoints for SSE, JSON-RPC, and health checks
Includes monitoring and error handling features
Supports integration with VS Code
The Benefits
Enables standardized AI-tool communication
Supports real-time messaging and diagnostics
Facilitates multi-language server implementations
Enhances developer productivity and tool interoperability
Model Context Protocol (MCP) Servers's Main Use Cases & Applications