Metoro MCP Server

Metoro MCP Server is a robust implementation of the Model Context Protocol (MCP) written in Go. It provides a standardized way for AI models to interact with external tools and services, enabling more powerful and context-aware AI applications. This server acts as a bridge between large language models and various tools, allowing models to perform actions beyond their training data.

Metoro MCP Server

Metoro MCP Server is a Go implementation of the Model Context Protocol (MCP), which enables AI models to interact with external tools and services in a standardized way.

Installation

To install and run the Metoro MCP Server, you have several options:

Option 1: Using Go

If you have Go installed, you can install and run the server directly:

# Clone the repository
git clone https://github.com/metoro-io/metoro-mcp-server.git
cd metoro-mcp-server

# Build and run
go build
./metoro-mcp-server

Option 2: Using Docker

You can also run the server using Docker:

docker run -p 8080:8080 metoro/metoro-mcp-server

Configuration

The server can be configured using environment variables:

PORT: The port on which the server will listen (default: 8080)
HOST: The host address to bind to (default: 0.0.0.0)
LOG_LEVEL: Logging level (default: info)

Usage

Once the server is running, it will expose an HTTP API that follows the Model Context Protocol specification. AI models can connect to this server to access various tools and functionalities.

To use the Metoro MCP Server with your AI application:

Start the server using one of the installation methods above
Configure your AI client to connect to the server endpoint (typically http://localhost:8080)
The AI can now make requests to the server to use the available tools

Kubernetes Deployment

For production environments, Kubernetes resources are available in the repository to help you deploy the server at scale. These resources include deployments, services, and configuration maps to manage the server in a Kubernetes cluster.

Development

If you want to contribute to the project or extend it with your own tools:

Fork the repository
Make your changes
Submit a pull request

The codebase is structured to be modular, making it easy to add new tools and functionalities.

Troubleshooting

If you encounter issues:

Check the server logs for error messages
Verify that your client is correctly configured to connect to the server
Ensure that the required environment variables are set properly
For network-related issues, check that the server port is accessible from your client

Metoro MCP Server

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