Deploy MCP servers in AgentCore Runtime
Amazon Bedrock AgentCore Runtime lets you deploy and run Model Context Protocol (MCP) servers in the AgentCore Runtime. This guide walks you through creating, testing, and deploying your first MCP server.
For an example, see https://github.com/awslabs/amazon-bedrock-agentcore-samples/tree/main/01-tutorials/01-AgentCore-runtime/02-hosting-MCP-server
In this section, you learn:
-
How to create an MCP server with tools
-
How to test your server locally
-
How to deploy your server to AWS
-
How to invoke your deployed server
For more information about MCP, see MCP protocol contract.
Topics
How Amazon Bedrock AgentCore supports MCP
When you configure a Amazon Bedrock AgentCore Runtime with the MCP protocol, the service
expects MCP server containers to be available at the path 0.0.0.0:8000/mcp,
which is the default path supported by most official MCP server SDKs.
Amazon Bedrock AgentCore requires stateless streamable-HTTP servers because the Runtime
provides session isolation by default. The platform automatically adds a
Mcp-Session-Id header for any request without it, so MCP clients can
maintain connection continuity to the same Amazon Bedrock AgentCore Runtime session.
The payload of the InvokeAgentRuntime API is passed through directly, allowing RPC messages of protocols like MCP to be easily proxied.
Prerequisites
-
Python 3.10 or higher installed and basic understanding of Python
-
An AWS account with appropriate permissions and local credentials configured
Step 1: Create your MCP server
Install required packages
First, install the MCP package:
pip install mcp
Create your first MCP server
Create a new file called my_mcp_server.py:
# my_mcp_server.py from mcp.server.fastmcp import FastMCP from starlette.responses import JSONResponse mcp = FastMCP(host="0.0.0.0", stateless_http=True) @mcp.tool() def add_numbers(a: int, b: int) -> int: """Add two numbers together""" return a + b @mcp.tool() def multiply_numbers(a: int, b: int) -> int: """Multiply two numbers together""" return a * b @mcp.tool() def greet_user(name: str) -> str: """Greet a user by name""" return f"Hello, {name}! Nice to meet you." if __name__ == "__main__": mcp.run(transport="streamable-http")
Understanding the code
-
FastMCP: Creates an MCP server that can host your tools
-
@mcp.tool(): Decorator that turns your Python functions into MCP tools
-
Tools: Three simple tools that demonstrate different types of operations
Step 2: Test your MCP server locally
Start your MCP server
Run your MCP server locally:
python my_mcp_server.py
You should see output indicating the server is running on port
8000.
Test with MCP client
From a new terminal, create a new file my_mcp_client.py and
execute it using python my_mcp_client.py
# my_mcp_client.py import asyncio from mcp import ClientSession from mcp.client.streamable_http import streamablehttp_client async def main(): mcp_url = "http://localhost:8000/mcp" headers = {} async with streamablehttp_client(mcp_url, headers, timeout=120, terminate_on_close=False) as ( read_stream, write_stream, _, ): async with ClientSession(read_stream, write_stream) as session: await session.initialize() tool_result = await session.list_tools() print(tool_result) asyncio.run(main())
You can also test your server using the MCP Inspector as described in Local testing with MCP inspector.
Step 3: Deploy your MCP server to AWS
Install deployment tools
Install the AgentCore starter toolkit:
pip install bedrock-agentcore-starter-toolkit
You use the starter toolkit to deploy your agent to AgentCore Runtime.
Create a project folder with the following structure:
## Project Folder Structure your_project_directory/ ├── mcp_server.py # Your main agent code ├── requirements.txt # Dependencies for your agent └── __init__.py # Makes the directory a Python package
Create a new file called requirements.txt, add the following
to it:
mcp
requirements.txt specifies the requirements that the agent needs for deployment to AgentCore Runtime.
Configure your MCP server for deployment
Before configuring your deployment, you need to set up a Cognito user pool for authentication as described in Set up Cognito user pool for authentication. This provides the OAuth tokens required for secure access to your deployed server.
Service-Linked Role for Authentication
Starting October 7, 2025, Amazon Bedrock AgentCore uses a Service-Linked Role for workload identity permissions when using OAuth authentication. For detailed information about this change, see Identity service-linked role.
After setting up authentication, create the deployment configuration:
agentcore configure -e my_mcp_server.py --protocol MCP
This will start a guided prompt workflow:
-
For execution role, you need to have an IAM execution role with appropriate permissions
-
For ECR, just press
enterto skip and it will auto-create -
For dependency file, the CLI will auto-detect from current directory
-
For OAuth, type
yesand provide the discovery URL and client ID token
Deploy to AWS
Deploy your agent:
agentcore launch
This command will:
-
Build a Docker container with your agent
-
Push it to Amazon ECR
-
Create a Amazon Bedrock AgentCore runtime
-
Deploy your agent to AWS
After deployment, you'll receive an agent runtime ARN that looks like:
arn:aws:bedrock-agentcore:us-west-2:accountId:runtime/my_mcp_server-xyz123
Step 4: Invoke your deployed MCP server
Test with MCP client (remote)
Before testing, set the following environment variables:
-
Export agent ARN as an environment variable:
export AGENT_ARN="agent_arn" -
Export bearer token as an environment variable:
export BEARER_TOKEN="bearer_token"
if you pass in an Accept header, it must follow the MCPapplication/json and text/event-stream.
Create a new file my_mcp_client_remote.py and execute it
using python my_mcp_client_remote.py
import asyncio import os import sys from mcp import ClientSession from mcp.client.streamable_http import streamablehttp_client async def main(): agent_arn = os.getenv('AGENT_ARN') bearer_token = os.getenv('BEARER_TOKEN') if not agent_arn or not bearer_token: print("Error: AGENT_ARN or BEARER_TOKEN environment variable is not set") sys.exit(1) encoded_arn = agent_arn.replace(':', '%3A').replace('/', '%2F') mcp_url = f"https://bedrock-agentcore.us-west-2.amazonaws.com/runtimes/{encoded_arn}/invocations?qualifier=DEFAULT" headers = {"authorization": f"Bearer {bearer_token}","Content-Type":"application/json"} print(f"Invoking: {mcp_url}, \nwith headers: {headers}\n") async with streamablehttp_client(mcp_url, headers, timeout=120, terminate_on_close=False) as ( read_stream, write_stream, _, ): async with ClientSession(read_stream, write_stream) as session: await session.initialize() tool_result = await session.list_tools() print(tool_result) asyncio.run(main())
You can also test your deployed server using the MCP Inspector as described in Remote testing with MCP inspector.
Authentication Error Responses for OAuth-Configured Agents
OAuth-configured agents follow RFC 6749 (OAuth 2.0)
401 Unauthorized - Missing Authentication
When no Bearer token is provided in the Authorization header, the response is:
HTTP/1.1 401 Unauthorized WWW-Authenticate: Bearer resource_metadata="https://bedrock-agentcore.{region}.amazonaws.com/runtimes/{ESCAPED_ARN}/invocations/.well-known/oauth-protected-resource?qualifier={QUALIFIER}"
End to End Flow with Auth0
This section demonstrates OAuth authentication using Auth0 as the identity provider. We use Auth0 for this example because it supports Dynamic Client Registration (DCR), which simplifies the client setup process by allowing clients to register themselves programmatically at runtime.
Step 1 - Step 3: Create and test your MCP server
Follow Steps 1-3 from Step 1: Create your MCP server through Step 3: Deploy your MCP server to AWS to create and test your MCP server.
Step 4: Create Auth0 application
Follow the Auth0 setup instructions at Auth0 by Okta.
Enable Dynamic Client Registration:
-
Dashboard → Settings → Advanced
-
Toggle "OIDC Dynamic Application Registration" → ON
-
Save changes
For more information, see Auth0 Dynamic Client Registration documentation
Step 5: Configure your MCP server for deployment
After setting up authentication, create the deployment configuration:
agentcore configure -e my_mcp_server.py --protocol MCP
This will start a guided prompt workflow:
-
For execution role, you need to have an IAM execution role with appropriate permissions
-
For ECR, just press
enterto skip and it will auto-create -
For OAuth, type
yesand provide the discovery URL and audience.
Step 6: Deploy to AWS
Deploy your agent:
agentcore launch
This command will:
-
Build a Docker container with your agent
-
Push it to Amazon ECR
-
Create a Amazon Bedrock AgentCore runtime
-
Deploy your agent to AWS
After deployment, you'll receive an agent runtime ARN that looks like:
arn:aws:bedrock-agentcore:us-west-2:accountId:runtime/my_mcp_server-xyz123
Step 7: Invoke your deployed Agent
This client is based on the official MCP SDK simple-auth-client example
Auth0 Audience Parameter Requirement
When using Auth0 with Dynamic Client Registration, you must include the audience parameter in authorization requests to receive JWT tokens. Without this parameter, Auth0 returns opaque tokens or JWE (encrypted) tokens instead of standard JWT tokens. The MCP SDK sends OAuth 2.0's resource parameter (RFC 8707), but Auth0 requires the OIDC audience parameter for JWT tokens. Both parameters serve similar purposes but Auth0 prioritizes audience. For more information, see Auth0 Community - JWT tokens with Dynamic Application Registration
Create a file named mcp_auth0_client.py with the following code. This client handles Auth0-specific requirements including the audience parameter:
Note
The code includes httpx patching to inject User-Agent headers into all HTTP requests. This is necessary because the MCP Python SDK currently does not include User-Agent headers in its HTTP requests, which can cause issues with AWS WAF rules that require User-Agent headers. For more information, see MCP Python SDK Issue #1664
#!/usr/bin/env python3 """ MCP client with OAuth authentication support for Auth0. Based on the official MCP SDK simple-auth-client example with Auth0 compatibility. Adds support for Auth0's 'audience' parameter requirement. Usage: # Required export AGENT_ARN="arn:aws:bedrock:us-west-2:123456789012:agent/ABCD1234" # Required for Auth0 export AUTH0_API_IDENTIFIER="your-api-identifier" # Optional - custom endpoint for beta/dev environments export CUSTOM_ENDPOINT="https://beta.example.com" python mcp_auth0_client.py The client will automatically: - Encode the Agent ARN for use in the URL - Construct the MCP invocation endpoint URL - Add Auth0 'audience' parameter to authorization requests (when using Auth0) - Work with any OAuth 2.0 compliant identity provider """ import asyncio import httpx import os import threading import time import webbrowser from datetime import timedelta from http.server import BaseHTTPRequestHandler, HTTPServer from typing import Any from urllib.parse import parse_qs, urlencode, urlparse, urlunparse # Patch httpx at the request level to inject User-Agent header # This ensures ALL HTTP requests have the User-Agent header, including OAuth discovery calls _original_httpx_request = httpx.Request.__init__ def _patched_httpx_request_init(self, method, url, *args, **kwargs): """Patched Request.__init__ that injects User-Agent header into all HTTP requests.""" # Get or create headers headers = kwargs.get('headers') if headers is None: headers = {} kwargs['headers'] = headers # Convert to mutable dict if needed if not isinstance(headers, dict): headers = dict(headers) kwargs['headers'] = headers # Inject User-Agent if not present (case-insensitive check) if 'User-Agent' not in headers and 'user-agent' not in headers: headers['User-Agent'] = 'python-mcp-sdk/1.0 (BedrockAgentCore-Runtime)' # Call original __init__ _original_httpx_request(self, method, url, *args, **kwargs) # Apply the patch globally before importing MCP modules httpx.Request.__init__ = _patched_httpx_request_init # Now import MCP modules - they will use patched httpx from mcp.client.auth import OAuthClientProvider, TokenStorage from mcp.client.session import ClientSession from mcp.client.sse import sse_client from mcp.client.streamable_http import streamablehttp_client from mcp.shared.auth import OAuthClientInformationFull, OAuthClientMetadata, OAuthToken class InMemoryTokenStorage(TokenStorage): """Simple in-memory token storage implementation.""" def __init__(self): self._tokens: OAuthToken | None = None self._client_info: OAuthClientInformationFull | None = None async def get_tokens(self) -> OAuthToken | None: return self._tokens async def set_tokens(self, tokens: OAuthToken) -> None: self._tokens = tokens async def get_client_info(self) -> OAuthClientInformationFull | None: return self._client_info async def set_client_info(self, client_info: OAuthClientInformationFull) -> None: self._client_info = client_info class CallbackHandler(BaseHTTPRequestHandler): """Simple HTTP handler to capture OAuth callback.""" def __init__(self, request, client_address, server, callback_data): """Initialize with callback data storage.""" self.callback_data = callback_data super().__init__(request, client_address, server) def do_GET(self): """Handle GET request from OAuth redirect.""" parsed = urlparse(self.path) query_params = parse_qs(parsed.query) if "code" in query_params: self.callback_data["authorization_code"] = query_params["code"][0] self.callback_data["state"] = query_params.get("state", [None])[0] self.send_response(200) self.send_header("Content-type", "text/html") self.end_headers() self.wfile.write(b""" <html> <body> <h1>Authorization Successful!</h1> <p>You can close this window and return to the terminal.</p> <script>setTimeout(() => window.close(), 2000);</script> </body> </html> """) elif "error" in query_params: self.callback_data["error"] = query_params["error"][0] self.send_response(400) self.send_header("Content-type", "text/html") self.end_headers() self.wfile.write( f""" <html> <body> <h1>Authorization Failed</h1> <p>Error: {query_params["error"][0]}</p> <p>You can close this window and return to the terminal.</p> </body> </html> """.encode() ) else: self.send_response(404) self.end_headers() def log_message(self, format, *args): """Suppress default logging.""" pass class CallbackServer: """Simple server to handle OAuth callbacks.""" def __init__(self, port=3030): self.port = port self.server = None self.thread = None self.callback_data = {"authorization_code": None, "state": None, "error": None} def _create_handler_with_data(self): """Create a handler class with access to callback data.""" callback_data = self.callback_data class DataCallbackHandler(CallbackHandler): def __init__(self, request, client_address, server): super().__init__(request, client_address, server, callback_data) return DataCallbackHandler def start(self): """Start the callback server in a background thread.""" handler_class = self._create_handler_with_data() self.server = HTTPServer(("localhost", self.port), handler_class) self.thread = threading.Thread(target=self.server.serve_forever, daemon=True) self.thread.start() print(f"🖥️ Started callback server on http://localhost:{self.port}") def stop(self): """Stop the callback server.""" if self.server: self.server.shutdown() self.server.server_close() if self.thread: self.thread.join(timeout=1) def wait_for_callback(self, timeout=300): """Wait for OAuth callback with timeout.""" start_time = time.time() while time.time() - start_time < timeout: if self.callback_data["authorization_code"]: return self.callback_data["authorization_code"] elif self.callback_data["error"]: raise Exception(f"OAuth error: {self.callback_data['error']}") time.sleep(0.1) raise Exception("Timeout waiting for OAuth callback") def get_state(self): """Get the received state parameter.""" return self.callback_data["state"] def add_auth0_audience_parameter(authorization_url: str, audience: str) -> str: """ Add Auth0 'audience' parameter to authorization URL. Auth0 requires the 'audience' parameter to identify which API's token settings to use. Without it, Auth0 returns opaque tokens or JWE instead of JWT. This function properly adds the audience parameter while preserving all existing query parameters (including the OAuth 'resource' parameter). Args: authorization_url: The authorization URL from the OAuth flow audience: The Auth0 API identifier (e.g., "runtime-api") Returns: Modified URL with audience parameter added Reference: https://auth0.com/docs/secure/tokens/access-tokens/get-access-tokens """ # Only apply to Auth0 URLs that don't already have audience if 'auth0.com' not in authorization_url or 'audience=' in authorization_url: return authorization_url # Parse URL and query parameters parsed = urlparse(authorization_url) query_params = parse_qs(parsed.query, keep_blank_values=True) # Add audience parameter query_params['audience'] = [audience] # Rebuild URL with new parameter new_query = urlencode(query_params, doseq=True) return urlunparse(( parsed.scheme, parsed.netloc, parsed.path, parsed.params, new_query, parsed.fragment )) class SimpleAuthClient: """Simple MCP client with Auth0 OAuth support.""" def __init__( self, server_url: str, transport_type: str = "streamable-http", auth0_audience: str | None = None, ): self.server_url = server_url self.transport_type = transport_type self.auth0_audience = auth0_audience self.session: ClientSession | None = None async def connect(self): """Connect to the MCP server.""" print(f"🔗 Attempting to connect to {self.server_url}...") try: callback_server = CallbackServer(port=3030) callback_server.start() async def callback_handler() -> tuple[str, str | None]: """Wait for OAuth callback and return auth code and state.""" print("⏳ Waiting for authorization callback...") try: auth_code = callback_server.wait_for_callback(timeout=300) return auth_code, callback_server.get_state() finally: callback_server.stop() client_metadata_dict = { "client_name": "MCP Auth0 Client", "redirect_uris": ["http://localhost:3030/callback"], "grant_types": ["authorization_code", "refresh_token"], "response_types": ["code"], } async def redirect_handler(authorization_url: str) -> None: """Redirect handler that opens the URL in a browser with Auth0 audience parameter.""" # Add Auth0 audience parameter if configured if self.auth0_audience: authorization_url = add_auth0_audience_parameter( authorization_url, self.auth0_audience ) webbrowser.open(authorization_url) print("\n🔧 Creating OAuth client provider...") # Create OAuth authentication handler # Note: httpx.AsyncClient is globally patched to inject User-Agent header oauth_auth = OAuthClientProvider( server_url=self.server_url, client_metadata=OAuthClientMetadata.model_validate(client_metadata_dict), storage=InMemoryTokenStorage(), redirect_handler=redirect_handler, callback_handler=callback_handler, ) print("🔧 OAuth client provider created successfully") # Create transport with auth handler based on transport type if self.transport_type == "sse": print("📡 Opening SSE transport connection with auth...") async with sse_client( url=self.server_url, auth=oauth_auth, timeout=60, ) as (read_stream, write_stream): await self._run_session(read_stream, write_stream, None) else: print("📡 Opening StreamableHTTP transport connection with auth...") async with streamablehttp_client( url=self.server_url, auth=oauth_auth, timeout=timedelta(seconds=60), ) as (read_stream, write_stream, get_session_id): await self._run_session(read_stream, write_stream, get_session_id) except Exception as e: print(f"❌ Failed to connect: {e}") import traceback traceback.print_exc() async def _run_session(self, read_stream, write_stream, get_session_id): """Run the MCP session with the given streams.""" print("🤝 Initializing MCP session...") async with ClientSession(read_stream, write_stream) as session: self.session = session print("⚡ Starting session initialization...") await session.initialize() print("✨ Session initialization complete!") print(f"\n✅ Connected to MCP server at {self.server_url}") if get_session_id: session_id = get_session_id() if session_id: print(f"Session ID: {session_id}") # Run interactive loop await self.interactive_loop() async def list_tools(self): """List available tools from the server.""" if not self.session: print("❌ Not connected to server") return try: result = await self.session.list_tools() if hasattr(result, "tools") and result.tools: print("\n📋 Available tools:") for i, tool in enumerate(result.tools, 1): print(f"{i}. {tool.name}") if tool.description: print(f" Description: {tool.description}") print() else: print("No tools available") except Exception as e: print(f"❌ Failed to list tools: {e}") async def call_tool(self, tool_name: str, arguments: dict[str, Any] | None = None): """Call a specific tool.""" if not self.session: print("❌ Not connected to server") return try: result = await self.session.call_tool(tool_name, arguments or {}) print(f"\n🔧 Tool '{tool_name}' result:") if hasattr(result, "content"): for content in result.content: if content.type == "text": print(content.text) else: print(content) else: print(result) except Exception as e: print(f"❌ Failed to call tool '{tool_name}': {e}") async def interactive_loop(self): """Run interactive command loop.""" print("\n🎯 Interactive MCP Client") print("Commands:") print(" list - List available tools") print(" call <tool_name> [args] - Call a tool") print(" quit - Exit the client") print() while True: try: command = input("mcp> ").strip() if not command: continue if command == "quit": break elif command == "list": await self.list_tools() elif command.startswith("call "): parts = command.split(maxsplit=2) tool_name = parts[1] if len(parts) > 1 else "" if not tool_name: print("❌ Please specify a tool name") continue # Parse arguments (simple JSON-like format) arguments = {} if len(parts) > 2: import json try: arguments = json.loads(parts[2]) except json.JSONDecodeError: print("❌ Invalid arguments format (expected JSON)") continue await self.call_tool(tool_name, arguments) else: print("❌ Unknown command. Try 'list', 'call <tool_name>', or 'quit'") except KeyboardInterrupt: print("\n\n👋 Goodbye!") break except EOFError: break async def main(): """Main entry point.""" # Get Agent ARN from environment agent_arn = os.getenv("AGENT_ARN") if not agent_arn: print("❌ Please set AGENT_ARN environment variable") print("Example: export AGENT_ARN='arn:aws:bedrock:us-west-2:123456789012:agent/ABCD1234'") return # Encode the ARN for use in URL encoded_arn = agent_arn.replace(':', '%3A').replace('/', '%2F') # Get base URL - use custom endpoint or default to production base_endpoint = os.getenv("CUSTOM_ENDPOINT", "https://bedrock-agentcore.us-west-2.amazonaws.com") # Construct MCP URL from encoded ARN (no qualifier - SDK discovers it from PRM API) server_url = f"{base_endpoint}/runtimes/{encoded_arn}/invocations" # Get Auth0 configuration (required only for Auth0) auth0_audience = os.getenv("AUTH0_API_IDENTIFIER") # Get optional transport type transport_type = os.getenv("MCP_TRANSPORT_TYPE", "streamable-http") print("🚀 MCP Auth0 Client") print(f"Agent ARN: {agent_arn}") print(f"Endpoint: {base_endpoint}") print(f"Connecting to: {server_url}") print(f"Transport type: {transport_type}") if auth0_audience: print(f"Auth0 audience: {auth0_audience}") # Start connection flow - OAuth will be handled automatically client = SimpleAuthClient( server_url, transport_type, auth0_audience, ) await client.connect() def cli(): """CLI entry point for uv script.""" asyncio.run(main()) if __name__ == "__main__": cli()
To use the client:
-
Set required environment variables:
export AGENT_ARN="arn:aws:bedrock:us-west-2:123456789012:agent/ABCD1234" -
Set Auth0-specific environment variable (required only for Auth0):
export AUTH0_API_IDENTIFIER="your-api-identifier" -
Run the client:
python mcp_auth0_client.py
The client will automatically:
-
Encode the Agent ARN for use in the URL
-
Construct the MCP invocation endpoint URL
-
Add Auth0
audienceparameter to authorization requests (when using Auth0) -
Work with any OAuth 2.0 compliant identity provider
Appendix
Set up Cognito user pool for authentication
Create a new file setup_cognito.sh and add the following
content.
#!/bin/bash # Create User Pool and capture Pool ID directly export POOL_ID=$(aws cognito-idp create-user-pool \ --pool-name "MyUserPool" \ --policies '{"PasswordPolicy":{"MinimumLength":8}}' \ --region $REGION | jq -r '.UserPool.Id') # Create App Client and capture Client ID directly export CLIENT_ID=$(aws cognito-idp create-user-pool-client \ --user-pool-id $POOL_ID \ --client-name "MyClient" \ --no-generate-secret \ --explicit-auth-flows "ALLOW_USER_PASSWORD_AUTH" "ALLOW_REFRESH_TOKEN_AUTH" \ --region $REGION | jq -r '.UserPoolClient.ClientId') # Create User aws cognito-idp admin-create-user \ --user-pool-id $POOL_ID \ --username $USERNAME \ --region $REGION \ --message-action SUPPRESS > /dev/null # Set Permanent Password aws cognito-idp admin-set-user-password \ --user-pool-id $POOL_ID \ --username $USERNAME \ --password $PASSWORD \ --region $REGION \ --permanent > /dev/null # Authenticate User and capture Access Token export BEARER_TOKEN=$(aws cognito-idp initiate-auth \ --client-id "$CLIENT_ID" \ --auth-flow USER_PASSWORD_AUTH \ --auth-parameters USERNAME=$USERNAME,PASSWORD=$PASSWORD \ --region $REGION | jq -r '.AuthenticationResult.AccessToken') # Output the required values echo "Pool id: $POOL_ID" echo "Discovery URL: https://cognito-idp.$REGION.amazonaws.com/$POOL_ID/.well-known/openid-configuration" echo "Client ID: $CLIENT_ID" echo "Bearer Token: $BEARER_TOKEN"
Open a terminal window and set the following environment variables:
REGION– the AWS Region that you want to useUSERNAME– the user name for the new userPASSWORD– the password for the new user
export REGION=us-east-1// set your desired Region export USERNAME=USER NAMEexport PASSWORD=PASSWORD
Run the script using the command source
setup_cognito.sh.
Note
For detailed OAuth authentication setup and Service-Linked Role information, see Authenticate and authorize with Inbound Auth and Outbound Auth.
After running this script, note the following values for use in the deployment configuration:
-
Discovery URL: Used during the
agentcore configurestep -
Client ID: Used during the
agentcore configurestep -
Bearer Token: Used when invoking your deployed server
Local testing with MCP inspector
The MCP Inspector is a visual tool for testing MCP servers. To use it, you need:
-
Node.js and npm installed
Install and run the MCP Inspector:
npx @modelcontextprotocol/inspector
This will:
-
Start the MCP Inspector server
-
Display a URL in your terminal (typically
http://localhost:6274)
To use the Inspector:
-
Navigate to
http://localhost:6274in your browser -
Paste the MCP server URL (
http://localhost:8000/mcp) into the MCP Inspector connection field -
You'll see your tools listed in the sidebar
-
Click on any tool to test it
-
Fill in the parameters (e.g., for
add_numbers, enter values foraandb) -
Click "Call Tool" to see the result
Remote testing with MCP inspector
You can also test your deployed server using the MCP Inspector:
-
Open the MCP Inspector:
npx @modelcontextprotocol/inspector -
In the web interface:
-
Select "Streamable HTTP" as the transport
-
Enter your agent's endpoint URL, which will look like:
https://bedrock-agentcore.us-west-2.amazonaws.com/runtimes/arn%3Aaws%3Abedrock-agentcore%3Aus-west-2%3AaccountId%3Aruntime%2FruntimeName/invocations?qualifier=DEFAULT -
Make sure to URL-encode your agent runtime ARN when constructing the endpoint URL. The colon (:) characters become %3A and forward slashes (/) become %2F in the encoded URL.
-
Add your Bearer token under authentication
-
Click "Connect"
-
-
Test your tools just like you did locally