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Tes Server

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Exposes public weather and climate data through a standardized API, allowing AI agents to retrieve current conditions, 7-day forecasts, and historical data. It

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About

Exposes public weather and climate data through a standardized API, allowing AI agents to retrieve current conditions, 7-day forecasts, and historical data. It enables weather-aware automation and data enrichment for conversational agents and travel planning.

README

This is an MCP (Model Context Protocol) server that provides access to the tes-mcp-server API. It enables AI agents and LLMs to interact with tes-mcp-server through standardized tools.

Features

  • 🔧 MCP Protocol: Built on the Model Context Protocol for seamless AI integration
  • 🌐 Full API Access: Provides tools for interacting with tes-mcp-server endpoints
  • 🐳 Docker Support: Easy deployment with Docker and Docker Compose
  • Async Operations: Built with FastMCP for efficient async handling

API Documentation

Available Tools

This server provides the following tools:

  • example_tool: Placeholder tool (to be implemented)

Note: Replace example_tool with actual tes-mcp-server API tools based on the documentation.

Installation

Using Docker (Recommended)

  1. Clone this repository:

    git clone https://github.com/Traia-IO/tes-mcp-server-mcp-server.git
    cd tes-mcp-server-mcp-server
    
  2. Run with Docker:

    ./run_local_docker.sh
    

Using Docker Compose

  1. Create a .env file with your configuration:
    
    

PORT=8000


2. Start the server:
```bash
docker-compose up

Manual Installation

  1. Install dependencies using uv:

    uv pip install -e .
    
  2. Run the server:

    
    

uv run python -m server


## Usage

### Health Check

Test if the server is running:
```bash
python mcp_health_check.py

Using with CrewAI

from traia_iatp.mcp.traia_mcp_adapter import create_mcp_adapter

# Connect to the MCP server
with create_mcp_adapter(
    url="http://localhost:8000/mcp/"
) as tools:
    # Use the tools
    for tool in tools:
        print(f"Available tool: {tool.name}")
        
    # Example usage
    result = await tool.example_tool(query="test")
    print(result)

Development

Testing the Server

  1. Start the server locally
  2. Run the health check: python mcp_health_check.py
  3. Test individual tools using the CrewAI adapter

Adding New Tools

To add new tools, edit server.py and:

  1. Create API client functions for tes-mcp-server endpoints
  2. Add @mcp.tool() decorated functions
  3. Update this README with the new tools
  4. Update deployment_params.json with the tool names in the capabilities array

Deployment

Deployment Configuration

The deployment_params.json file contains the deployment configuration for this MCP server:

{
  "github_url": "https://github.com/Traia-IO/tes-mcp-server-mcp-server",
  "mcp_server": {
    "name": "tes-mcp-server-mcp",
    "description": "This mcp server exposes public weather and climate data through a standardized mcp-compatible api.
it allows ai agents to retrieve current weather conditions, 7-day forecasts, and historical climate data
for supported locations worldwide.

use cases include:
- ai-powered travel planning
- weather-aware automation
- data enrichment for conversational agents
",
    "server_type": "streamable-http",
"capabilities": [
      // List all implemented tool names here
      "example_tool"
    ]
  },
  "deployment_method": "cloud_run",
  "gcp_project_id": "traia-mcp-servers",
  "gcp_region": "us-central1",
  "tags": ["tes-mcp-server", "api"],
  "ref": "main"
}

Important: Always update the capabilities array when you add or remove tools!

Google Cloud Run

This server is designed to be deployed on Google Cloud Run. The deployment will:

  1. Build a container from the Dockerfile
  2. Deploy to Cloud Run with the specified configuration
  3. Expose the /mcp endpoint for client connections

Environment Variables

  • PORT: Server port (default: 8000)
  • STAGE: Environment stage (default: MAINNET, options: MAINNET, TESTNET)
  • LOG_LEVEL: Logging level (default: INFO)

Troubleshooting

  1. Server not starting: Check Docker logs with docker logs <container-id>
  2. Connection errors: Ensure the server is running on the expected port3. Tool errors: Check the server logs for detailed error messages

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Implement new tools or improvements
  4. Update the README and deployment_params.json
  5. Submit a pull request

License

MIT License

from github.com/Traia-IO/tes-mcp-server-mcp-server

Installing Tes Server

This server has no published package — it is built from source. Open the repository and follow its README.

▸ github.com/Traia-IO/tes-mcp-server-mcp-server

FAQ

Is Tes Server MCP free?

Yes, Tes Server MCP is free — one-click install via Unyly at no cost.

Does Tes Server need an API key?

No, Tes Server runs without API keys or environment variables.

Is Tes Server hosted or self-hosted?

A hosted option is available: Unyly runs the server in the cloud, no local setup required.

How do I install Tes Server in Claude Desktop, Claude Code or Cursor?

Open Tes Server on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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