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 multiple
10    Model Context Protocol (MCP) servers 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_multiple_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_1 - The URL of your first MCP server endpoint.
26    4) MCP_SERVER_LABEL_1 - A label for your first MCP server.
27    5) MCP_SERVER_URL_2 - The URL of your second MCP server endpoint.
28    6) MCP_SERVER_LABEL_2 - A label for your second MCP server.
29"""
30 
31import os, time
32from azure.ai.projects import AIProjectClient
33from azure.identity import DefaultAzureCredential
34from azure.ai.agents.models import (
35    ListSortOrder,
36    McpTool,
37    RequiredMcpToolCall,
38    RunStepActivityDetails,
39    SubmitToolApprovalAction,
40    ToolApproval,
41)
42 
43# Get MCP server configuration from environment variables
44mcp_server_url_1 = os.environ.get("MCP_SERVER_URL_1", "https://gitmcp.io/Azure/azure-rest-api-specs")
45mcp_server_label_1 = os.environ.get("MCP_SERVER_LABEL_1", "github")
46mcp_server_url_2 = os.environ.get("MCP_SERVER_URL_2", "https://learn.microsoft.com/api/mcp")
47mcp_server_label_2 = os.environ.get("MCP_SERVER_LABEL_2", "microsoft_learn")
48 
49project_client = AIProjectClient(
50    endpoint=os.environ["PROJECT_ENDPOINT"],
51    credential=DefaultAzureCredential(),
52)
53 
54# Initialize agent MCP tool
55mcp_tool1 = McpTool(
56    server_label=mcp_server_label_1,
57    server_url=mcp_server_url_1,
58    allowed_tools=[],  # Optional: specify allowed tools
59)
60 
61# You can also add or remove allowed tools dynamically
62search_api_code = "search_azure_rest_api_code"
63mcp_tool1.allow_tool(search_api_code)
64print(f"Allowed tools: {mcp_tool1.allowed_tools}")
65 
66mcp_tool2 = McpTool(
67    server_label=mcp_server_label_2,
68    server_url=mcp_server_url_2,
69    allowed_tools=["microsoft_docs_search"],  # Optional: specify allowed tools
70)
71 
72mcp_tools = [mcp_tool1, mcp_tool2]
73 
74# Create agent with MCP tool and process agent run
75with project_client:
76    agents_client = project_client.agents
77 
78    # Create a new agent.
79    # NOTE: To reuse existing agent, fetch it with get_agent(agent_id)
80    agent = agents_client.create_agent(
81        model=os.environ["MODEL_DEPLOYMENT_NAME"],
82        name="my-mcp-agent",
83        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.",
84        tools=[tool.definitions[0] for tool in mcp_tools],
85    )
86 
87    print(f"Created agent, ID: {agent.id}")
88    print(f"MCP Server 1: {mcp_tool1.server_label} at {mcp_tool1.server_url}")
89    print(f"MCP Server 2: {mcp_tool2.server_label} at {mcp_tool2.server_url}")
90 
91    # Create thread for communication
92    thread = agents_client.threads.create()
93    print(f"Created thread, ID: {thread.id}")
94 
95    # Create message to thread
96    message = agents_client.messages.create(
97        thread_id=thread.id,
98        role="user",
99        content="Please summarize the Azure REST API specifications Readme and Give me the Azure CLI commands to create an Azure Container App with a managed identity",
100    )
101    print(f"Created message, ID: {message.id}")
102 
103    # Create and process agent run in thread with MCP tools
104    mcp_tool1.update_headers("SuperSecret", "123456")
105    mcp_tool2.set_approval_mode("never")  # Disable approval for MS Learn MCP tool
106    tool_resources = McpTool.merge_resources(mcp_tools)
107    print(tool_resources)
108    run = agents_client.runs.create(thread_id=thread.id, agent_id=agent.id, tool_resources=tool_resources)
109    print(f"Created run, ID: {run.id}")
110 
111    while run.status in ["queued", "in_progress", "requires_action"]:
112        time.sleep(1)
113        run = agents_client.runs.get(thread_id=thread.id, run_id=run.id)
114 
115        if run.status == "requires_action" and isinstance(run.required_action, SubmitToolApprovalAction):
116            tool_calls = run.required_action.submit_tool_approval.tool_calls
117            if not tool_calls:
118                print("No tool calls provided - cancelling run")
119                agents_client.runs.cancel(thread_id=thread.id, run_id=run.id)
120                break
121 
122            tool_approvals = []
123            for tool_call in tool_calls:
124                if isinstance(tool_call, RequiredMcpToolCall):
125                    try:
126                        print(f"Approving tool call: {tool_call}")
127                        tool_approvals.append(
128                            ToolApproval(
129                                tool_call_id=tool_call.id,
130                                approve=True,
131                                headers=mcp_tool1.headers,
132                            )
133                        )
134                    except Exception as e:
135                        print(f"Error approving tool_call {tool_call.id}: {e}")
136 
137            print(f"tool_approvals: {tool_approvals}")
138            if tool_approvals:
139                agents_client.runs.submit_tool_outputs(
140                    thread_id=thread.id, run_id=run.id, tool_approvals=tool_approvals
141                )
142 
143        print(f"Current run status: {run.status}")
144 
145    print(f"Run completed with status: {run.status}")
146    if run.status == "failed":
147        print(f"Run failed: {run.last_error}")
148 
149    # Display run steps and tool calls
150    run_steps = agents_client.run_steps.list(thread_id=thread.id, run_id=run.id)
151 
152    # Loop through each step
153    for step in run_steps:
154        print(f"Step {step['id']} status: {step['status']}")
155 
156        # Check if there are tool calls in the step details
157        step_details = step.get("step_details", {})
158        tool_calls = step_details.get("tool_calls", [])
159 
160        if tool_calls:
161            print("  MCP Tool calls:")
162            for call in tool_calls:
163                print(f"    Tool Call ID: {call.get('id')}")
164                print(f"    Type: {call.get('type')}")
165 
166        if isinstance(step_details, RunStepActivityDetails):
167            for activity in step_details.activities:
168                for function_name, function_definition in activity.tools.items():
169                    print(
170                        f'  The function {function_name} with description "{function_definition.description}" will be called.:'
171                    )
172                    if len(function_definition.parameters) > 0:
173                        print("  Function parameters:")
174                        for argument, func_argument in function_definition.parameters.properties.items():
175                            print(f"      {argument}")
176                            print(f"      Type: {func_argument.type}")
177                            print(f"      Description: {func_argument.description}")
178                    else:
179                        print("This function has no parameters")
180 
181        print()  # add an extra newline between steps
182 
183    # Fetch and log all messages
184    messages = agents_client.messages.list(thread_id=thread.id, order=ListSortOrder.ASCENDING)
185    print("\nConversation:")
186    print("-" * 50)
187    for msg in messages:
188        if msg.text_messages:
189            last_text = msg.text_messages[-1]
190            print(f"{msg.role.upper()}: {last_text.text.value}")
191            print("-" * 50)
192 
193    # Example of dynamic tool management
194    print(f"\nDemonstrating dynamic tool management:")
195    print(f"Current allowed tools: {mcp_tool1.allowed_tools}")
196 
197    # Remove a tool
198    try:
199        mcp_tool1.disallow_tool(search_api_code)
200        print(f"After removing {search_api_code}: {mcp_tool1.allowed_tools}")
201    except ValueError as e:
202        print(f"Error removing tool: {e}")
203 
204    # Clean-up and delete the agent once the run is finished.
205    # NOTE: Comment out this line if you plan to reuse the agent later.
206    agents_client.delete_agent(agent.id)
207    print("Deleted agent")