1# pylint: disable=line-too-long,useless-suppression
2# ------------------------------------
3# Copyright (c) Microsoft Corporation.
4# Licensed under the MIT License.
5# ------------------------------------
6 
7"""
8DESCRIPTION:
9    This sample demonstrates how to use agent operations with the
10    Model Context Protocol (MCP) tool from the Azure Agents service using a synchronous client.
11    To learn more about Model Context Protocol, visit https://modelcontextprotocol.io/
12 
13USAGE:
14    python sample_agents_mcp.py
15 
16    Before running the sample:
17 
18    pip install azure-ai-projects azure-ai-agents>=1.2.0b3 azure-identity --pre
19 
20    Set these environment variables with your own values:
21    1) PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview
22                          page of your Azure AI Foundry portal.
23    2) MODEL_DEPLOYMENT_NAME - The deployment name of the AI model, as found under the "Name" column in
24       the "Models + endpoints" tab in your Azure AI Foundry project.
25    3) MCP_SERVER_URL - The URL of your MCP server endpoint.
26    4) MCP_SERVER_LABEL - A label for your MCP server.
27"""
28 
29import os, time
30from azure.ai.projects import AIProjectClient
31from azure.identity import DefaultAzureCredential
32from azure.ai.agents.models import (
33    ListSortOrder,
34    McpTool,
35    RequiredMcpToolCall,
36    RunStepActivityDetails,
37    SubmitToolApprovalAction,
38    ToolApproval,
39)
40 
41# Get MCP server configuration from environment variables
42mcp_server_url = os.environ.get("MCP_SERVER_URL", "https://gitmcp.io/Azure/azure-rest-api-specs")
43mcp_server_label = os.environ.get("MCP_SERVER_LABEL", "github")
44 
45project_client = AIProjectClient(
46    endpoint=os.environ["PROJECT_ENDPOINT"],
47    credential=DefaultAzureCredential(),
48)
49 
50# [START create_agent_with_mcp_tool]
51# Initialize agent MCP tool
52mcp_tool = McpTool(
53    server_label=mcp_server_label,
54    server_url=mcp_server_url,
55    allowed_tools=[],  # Optional: specify allowed tools
56)
57 
58# You can also add or remove allowed tools dynamically
59search_api_code = "search_azure_rest_api_code"
60mcp_tool.allow_tool(search_api_code)
61print(f"Allowed tools: {mcp_tool.allowed_tools}")
62 
63# Create agent with MCP tool and process agent run
64with project_client:
65    agents_client = project_client.agents
66 
67    # Create a new agent.
68    # NOTE: To reuse existing agent, fetch it with get_agent(agent_id)
69    agent = agents_client.create_agent(
70        model=os.environ["MODEL_DEPLOYMENT_NAME"],
71        name="my-mcp-agent",
72        instructions="You are a helpful agent that can use MCP tools to assist users. Use the available MCP tools to answer questions and perform tasks.",
73        tools=mcp_tool.definitions,
74    )
75    # [END create_agent_with_mcp_tool]
76 
77    print(f"Created agent, ID: {agent.id}")
78    print(f"MCP Server: {mcp_tool.server_label} at {mcp_tool.server_url}")
79 
80    # Create thread for communication
81    thread = agents_client.threads.create()
82    print(f"Created thread, ID: {thread.id}")
83 
84    # Create message to thread
85    message = agents_client.messages.create(
86        thread_id=thread.id,
87        role="user",
88        content="Please summarize the Azure REST API specifications Readme",
89    )
90    print(f"Created message, ID: {message.id}")
91 
92    # [START handle_tool_approvals]
93    # Create and process agent run in thread with MCP tools
94    mcp_tool.update_headers("SuperSecret", "123456")
95    # mcp_tool.set_approval_mode("never")  # Uncomment to disable approval requirement
96    run = agents_client.runs.create(thread_id=thread.id, agent_id=agent.id, tool_resources=mcp_tool.resources)
97    print(f"Created run, ID: {run.id}")
98 
99    while run.status in ["queued", "in_progress", "requires_action"]:
100        time.sleep(1)
101        run = agents_client.runs.get(thread_id=thread.id, run_id=run.id)
102 
103        if run.status == "requires_action" and isinstance(run.required_action, SubmitToolApprovalAction):
104            tool_calls = run.required_action.submit_tool_approval.tool_calls
105            if not tool_calls:
106                print("No tool calls provided - cancelling run")
107                agents_client.runs.cancel(thread_id=thread.id, run_id=run.id)
108                break
109 
110            tool_approvals = []
111            for tool_call in tool_calls:
112                if isinstance(tool_call, RequiredMcpToolCall):
113                    try:
114                        print(f"Approving tool call: {tool_call}")
115                        tool_approvals.append(
116                            ToolApproval(
117                                tool_call_id=tool_call.id,
118                                approve=True,
119                                headers=mcp_tool.headers,
120                            )
121                        )
122                    except Exception as e:
123                        print(f"Error approving tool_call {tool_call.id}: {e}")
124 
125            print(f"tool_approvals: {tool_approvals}")
126            if tool_approvals:
127                agents_client.runs.submit_tool_outputs(
128                    thread_id=thread.id, run_id=run.id, tool_approvals=tool_approvals
129                )
130 
131        print(f"Current run status: {run.status}")
132        # [END handle_tool_approvals]
133 
134    print(f"Run completed with status: {run.status}")
135    if run.status == "failed":
136        print(f"Run failed: {run.last_error}")
137 
138    # Display run steps and tool calls
139    run_steps = agents_client.run_steps.list(thread_id=thread.id, run_id=run.id)
140 
141    # Loop through each step
142    for step in run_steps:
143        print(f"Step {step['id']} status: {step['status']}")
144 
145        # Check if there are tool calls in the step details
146        step_details = step.get("step_details", {})
147        tool_calls = step_details.get("tool_calls", [])
148 
149        if tool_calls:
150            print("  MCP Tool calls:")
151            for call in tool_calls:
152                print(f"    Tool Call ID: {call.get('id')}")
153                print(f"    Type: {call.get('type')}")
154 
155        if isinstance(step_details, RunStepActivityDetails):
156            for activity in step_details.activities:
157                for function_name, function_definition in activity.tools.items():
158                    print(
159                        f'  The function {function_name} with description "{function_definition.description}" will be called.:'
160                    )
161                    if len(function_definition.parameters) > 0:
162                        print("  Function parameters:")
163                        for argument, func_argument in function_definition.parameters.properties.items():
164                            print(f"      {argument}")
165                            print(f"      Type: {func_argument.type}")
166                            print(f"      Description: {func_argument.description}")
167                    else:
168                        print("This function has no parameters")
169 
170        print()  # add an extra newline between steps
171 
172    # Fetch and log all messages
173    messages = agents_client.messages.list(thread_id=thread.id, order=ListSortOrder.ASCENDING)
174    print("\nConversation:")
175    print("-" * 50)
176    for msg in messages:
177        if msg.text_messages:
178            last_text = msg.text_messages[-1]
179            print(f"{msg.role.upper()}: {last_text.text.value}")
180            print("-" * 50)
181 
182    # Example of dynamic tool management
183    print(f"\nDemonstrating dynamic tool management:")
184    print(f"Current allowed tools: {mcp_tool.allowed_tools}")
185 
186    # Remove a tool
187    try:
188        mcp_tool.disallow_tool(search_api_code)
189        print(f"After removing {search_api_code}: {mcp_tool.allowed_tools}")
190    except ValueError as e:
191        print(f"Error removing tool: {e}")
192 
193    # Clean-up and delete the agent once the run is finished.
194    # NOTE: Comment out this line if you plan to reuse the agent later.
195    agents_client.delete_agent(agent.id)
196    print("Deleted agent")