FastMCP

#!/usr/bin/env python3 """ Example client script that demonstrates how to use the Model Context Protocol server """ import asyncio from fastmcp import Client async def main(): """Run example operations with the MCP server""" # Connect to the MCP server async with Client() as client: print("Connected to MCP server") # Check server health health = await client.call_tool("health_check") print(f"Server health: {health}") # Create a new context context_id = "example-context" create_result = await client.call_tool( "create_context", { "context_id": context_id, "model_name": "gpt-4", "data": {"parameters": {"temperature": 0.7, "max_tokens": 500}}, "tags": ["example", "demo"], }, ) print(f"Context creation result: {create_result}") # Get the context context = await client.call_tool("get_context", {"context_id": context_id}) print(f"Retrieved context: {context}") # List all contexts contexts = await client.call_tool("list_contexts") print(f"All contexts: {contexts}") # Filter contexts by tag tagged_contexts = await client.call_tool("list_contexts", {"tag": "example"}) print(f"Contexts with 'example' tag: {tagged_contexts}") # Execute a query query_result = await client.call_tool( "query_model", {"context_id": context_id, "query_data": {"prompt": "Hello, world!", "options": {"stream": False}}}, ) print(f"Query result: {query_result}") # Update the context update_result = await client.call_tool( "update_context", { "context_id": context_id, "model_name": "gpt-4", "data": {"parameters": {"temperature": 0.5, "max_tokens": 500}}, # Changed from 0.7 "tags": ["example", "demo", "updated"], # Added "updated" tag }, ) print(f"Context update result: {update_result}") # Delete the context delete_result = await client.call_tool("delete_context", {"context_id": context_id}) print(f"Context deletion result: {delete_result}") # Verify deletion contexts_after = await client.call_tool("list_contexts") print(f"Contexts after deletion: {contexts_after}") if __name__ == "__main__": # Run the async main function asyncio.run(main())