Skip to main content
Glama

AYX-MCP-Wrapper

by jupiterbak
test-workflow-Execution.py3.05 kB
import time import json import re from typing import List, Optional, Dict, Any from src.tools import AYXMCPTools, InputData from src.server_client.rest import ApiException def main(): """ Main function to demonstrate workflow execution functionality. """ workflow_id = "686358e9c04bebdd09cc95f1" # Example 1: Execute workflow without parameters print(f"1. Executing workflow: {workflow_id}") # Example input data (uncomment and modify as needed) # input_data = [ # InputData(name="parameter1", value="value1"), # InputData(name="parameter2", value="value2") # ] tools = AYXMCPTools() execution_result = tools.execute_workflow_with_monitoring( workflow_id=workflow_id, input_data=None, # Set to None for workflows without parameters wait_for_completion=True, timeout_seconds=300, # 5 minutes timeout poll_interval_seconds=10 ) print(execution_result) # if execution_result["success"]: # print("✅ Workflow executed successfully!") # print(f"Job ID: {execution_result['job_id']}") # print(f"Status: {execution_result['status']}") # print(f"Execution time: {execution_result.get('execution_time_seconds', 'N/A')} seconds") # if "job_messages" in execution_result: # print("\nJob messages:") # print(execution_result["job_messages"]) # else: # print("❌ Workflow execution failed!") # print(f"Error: {execution_result['error']}") # if execution_result.get('job_id'): # print(f"Job ID: {execution_result['job_id']}") # print("\n" + "="*50 + "\n") # # Example 2: Execute workflow with parameters (commented out) # print("2. Example: Executing workflow with parameters") # print("(This example is commented out - uncomment and modify as needed)") # # Uncomment and modify the following code to execute a workflow with parameters: # """ # # Example workflow with parameters # parameterized_workflow_id = "your-parameterized-workflow-id" # input_data = [ # InputData(name="input_file", value="/path/to/input.csv"), # InputData(name="output_file", value="/path/to/output.csv"), # InputData(name="filter_value", value="active") # ] # param_execution_result = execute_workflow_with_monitoring( # workflow_id=parameterized_workflow_id, # input_data=input_data, # wait_for_completion=True, # timeout_seconds=600, # 10 minutes timeout # poll_interval_seconds=5 # ) # if param_execution_result["success"]: # print("✅ Parameterized workflow executed successfully!") # print(f"Job ID: {param_execution_result['job_id']}") # else: # print("❌ Parameterized workflow execution failed!") # print(f"Error: {param_execution_result['error']}") # """ print("\n=== Demo completed ===") if __name__ == "__main__": main()

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/jupiterbak/AYX-MCP-Wrapper'

If you have feedback or need assistance with the MCP directory API, please join our Discord server