Test mcp server Traia

You can interact with the Test Traia MCP Server using the Model Context Protocol (MCP) to access Traia API tools through standardized endpoints. This enables AI agents and large language models to query, compose, and execute actions against the Traia API in a structured and scalable way.

How to use

Connect your MCP client to the server’s MCP endpoint to begin discovering and using available tools. The server exposes an MCP API that you can query to retrieve tool capabilities, then invoke specific tools to perform tasks described by their endpoints. In typical usage, you locate the MCP URL provided by your deployment, establish a session, and iterate through available tools to perform queries or actions relevant to your AI workflow.

How to install

Prerequisites: you need a working development environment with Docker, Python, and common command-line tools. Decide between a Docker-based deployment for quick startup or a manual setup for more control.

# Using Docker (Recommended)
# 1. Clone this repository
git clone https://github.com/Traia-IO/test-mcp-server-traia-mcp-server.git
cd test-mcp-server-traia-mcp-server

# 2. Run with Docker
./run_local_docker.sh

If you prefer Docker Compose, configure and start the server with a defined environment and compose orchestration.

# Using Docker Compose
# 1. Create a .env file with your configuration
PORT=8000

# 2. Start the server
docker-compose up

For a manual installation, install dependencies and run the server directly.

# Manual installation
uv pip install -e .

# Start the server
uv run python -m server

Deployment considerations

You can deploy this MCP server to Google Cloud Run. The deployment process builds a container from the Dockerfile, deploys to Cloud Run, and exposes the MCP endpoint at /mcp for client connections.

Environment variables

The server supports a set of environment variables to configure behavior across deployment environments.

Troubleshooting

If the server does not start, review the startup logs for errors. Common issues include port conflicts or missing dependencies. Ensure the server is reachable at the expected MCP URL and that firewall rules permit access to the port.

Notes and tips

When integrating with an MCP client, you may start by connecting to http://localhost:8000/mcp/ and enumerating available tools before executing actions. If you run the server locally, ensure port 8000 (or your chosen port) is open and mapped in your runtime environment.

Available tools

example_tool

Placeholder tool (to be implemented)