Which integrations are available for this server?

Provides access to the tesy 56 API endpoints through the [Swagger](/mcp/servers/integrations/swagger)/Petstore API, enabling AI agents to interact with the tesy 56 service programmatically.

tesy 56 MCP Server

This is an MCP (Model Context Protocol) server that provides access to the tesy 56 API. It enables AI agents and LLMs to interact with tesy 56 through standardized tools.

Features

🔧 MCP Protocol: Built on the Model Context Protocol for seamless AI integration
🌐 Full API Access: Provides tools for interacting with tesy 56 endpoints
🐳 Docker Support: Easy deployment with Docker and Docker Compose
⚡ Async Operations: Built with FastMCP for efficient async handling

API Documentation

tesy 56 Website: https://petstore.swagger.io/
API Documentation:

Available Tools

This server provides the following tools:

example_tool: Placeholder tool (to be implemented)

Note: Replace

Installation

Using Docker (Recommended)

Clone this repository:
git clone https://github.com/Traia-IO/tesy-56-mcp-server.git cd tesy-56-mcp-server
Run with Docker:
./run_local_docker.sh

Using Docker Compose

Create a .env file with your configuration:

PORT=8000

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

Manual Installation

Install dependencies using uv:
uv pip install -e .
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

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

Adding New Tools

To add new tools, edit server.py and:

Create API client functions for tesy 56 endpoints
Add @mcp.tool() decorated functions
Update this README with the new tools
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/tesy-56-mcp-server", "mcp_server": { "name": "tesy-56-mcp", "description": "Uih uih uhoui houiho", "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": ["tesy 56", "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:

Build a container from the Dockerfile
Deploy to Cloud Run with the specified configuration
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

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