Add a target using the API - Amazon Bedrock AgentCore

Add a target using the API

To add a target using the API, make a CreateGatewayTarget request with one of the AgentCore control plane endpoints.

Note

To add an integration provider template as a gateway target, you must use the the console. For more information, see Built-in templates from integration providers as targets.

Select a topic to see examples of adding a target type:

Add a Lambda target

If you use the AgentCore starter toolkit (either the CLI or the Python SDK), you can add a Lambda target to your gateway by specifying the --target_type as lambda and omitting all optional arguments. The default Lambda function and accompanying tool schema can be found in the AgentCore starter toolkit github.

Target configuration

The target configuration (or payload) for a Lambda function contains the following fields:

  • lambdaArn – The ARN of the Lambda function to use as your target.

  • toolSchema – The tool schema for the gateway target.

For more information about Lambda targets, see AWS Lambda function targets.

Select one of the following methods:

AgentCore starter toolkit (CLI)
Add a default Lambda function as a target

To add the default Lambda function as a target to your gateway in the AgentCore starter toolkit CLI, run the create_mcp_gateway_target command and specify the --target_type argument as lambda. The following example shows the minimum arguments you can provide:

agentcore create_mcp_gateway_target \ --gateway-arn arn:aws:bedrock-agentcore:us-east-1:123456789012:gateway/my-gateway \ --gateway-url https://gateway-id.gateway.bedrock-agentcore.us-west-2.amazonaws.com/mcp \ --role-arn arn:aws:iam::123456789012:role/AgentCoreGatewayExecutionRole \ --target-type lambda
AgentCore starter toolkit (Python)

With the AgentCore starter toolkit, you can easily create a Lambda target with default configurations.s

# Import dependencies from bedrock_agentcore_starter_toolkit.operations.gateway.client import GatewayClient # Initialize the client client = GatewayClient(region_name="us-east-1") # Create a lambda target. lambda_target = client.create_mcp_gateway_target( gateway=gateway, name=None, # If you don't set one, one will be generated. target_type="lambda", target_payload=None, # Define your own lambda if you pre-created one. Otherwise leave this as None and one will be created for you. credentials=None, # If you leave this as None, one will be created for you )

The following is an example argument you can provide for the target_payload. If you omit the target_payload argument, this payload is used:

{ "lambdaArn": "<insert your lambda arn>", "toolSchema": { "inlinePayload": [ { "name": "get_weather", "description": "Get weather for a location", "inputSchema": { "type": "object", "properties": { "location": { "type": "string", "description": "the location e.g. seattle, wa" } }, "required": [ "location" ] } }, { "name": "get_time", "description": "Get time for a timezone", "inputSchema": { "type": "object", "properties": { "timezone": { "type": "string" } }, "required": [ "timezone" ] } } ] } }
Boto3

The following Python code shows how to add a Lambda target using the AWS Python SDK (Boto3):

import boto3 # Create the agentcore client agentcore_client = boto3.client('bedrock-agentcore-control') # Create a Lambda target target = agentcore_client.create_gateway_target( gatewayIdentifier="your-gateway-id", name="LambdaTarget", targetConfiguration={ "mcp": { "lambda": { "lambdaArn": "arn:aws:lambda:us-west-2:123456789012:function:YourLambdaFunction", "toolSchema": { "inlinePayload": [ { "name": "get_weather", "description": "Get weather for a location", "inputSchema": { "type": "object", "properties": {"location": {"type": "string"}}, "required": ["location"], }, }, { "name": "get_time", "description": "Get time for a timezone", "inputSchema": { "type": "object", "properties": {"timezone": {"type": "string"}}, "required": ["timezone"], }, }, ] } } } }, credentialProviderConfigurations=[ { "credentialProviderType": "GATEWAY_IAM_ROLE" } ] )

Add an OpenAPI target

Select one of the following methods:

AgentCore starter toolkit
Example with S3 definition and API key outbound authorization

The following example demonstrates adding an OpenAPI schema target to a gateway. The schema has been uploaded to an S3 location whose URI is referenced in the target_payload. Outbound authorization for the target is through an API key.

# Import dependencies from bedrock_agentcore_starter_toolkit.operations.gateway.client import GatewayClient # Initialize the client gateway_client = GatewayClient(region_name="us-west-2") # Create an OpenAPI target with API Key authentication open_api_target = gateway_client.create_mcp_gateway_target( gateway="your-gateway-id", target_type="openApiSchema", target_payload={ "s3": { "uri": "s3://your-bucket/path/to/open-api-spec.json" } }, credentials={ "api_key": "your-api-key", "credential_location": "HEADER", "credential_parameter_name": "X-API-Key" } )
Example with S3 definition and OAuth outbound authorization

The following example demonstrates adding an OpenAPI schema target to a gateway. The schema has been uploaded to an S3 location whose URI is referenced in the target_payload. Outbound authorization for the target is through an OAuth.

# Import dependencies from bedrock_agentcore_starter_toolkit.operations.gateway.client import GatewayClient # Initialize the client gateway_client = GatewayClient(region_name="us-west-2") # Create an OpenAPI target with OAuth authentication open_api_with_oauth_target = gateway_client.create_mcp_gateway_target( gateway="your-gateway-id", target_type="openApiSchema", target_payload={ "s3": { "uri": "s3://your-bucket/path/to/open-api-spec.json" } }, credentials={ "oauth2_provider_config": { "customOauth2ProviderConfig": { "oauthDiscovery": { "authorizationServerMetadata": { "issuer": "https://example.auth0.com", "authorizationEndpoint": "https://example.auth0.com/authorize", "tokenEndpoint": "https://example.auth0.com/oauth/token" } }, "clientId": "your-client-id", "clientSecret": "your-client-secret" } } } )
Boto3

The following Python code shows how to add an OpenAPI target using the AWS Python SDK (Boto3). The schema has been uploaded to an S3 location whose URI is referenced in the target_payload. Outbound authorization for the target is through an API key.

import boto3 # Create the client agentcore_client = boto3.client('bedrock-agentcore-control') # Create an OpenAPI target with API Key authentication target = agentcore_client.create_gateway_target( gatewayIdentifier="your-gateway-id", name="SearchAPITarget", targetConfiguration={ "mcp": { "openApiSchema": { "s3": { "uri": "s3://your-bucket/path/to/open-api-spec.json", "bucketOwnerAccountId": "123456789012" } } } }, credentialProviderConfigurations=[ { "credentialProviderType": "API_KEY", "credentialProvider": { "apiKeyCredentialProvider": { "providerArn": "arn:aws:agent-credential-provider:us-east-1:123456789012:token-vault/default/apikeycredentialprovider/abcdefghijk", "credentialLocation": "HEADER", "credentialParameterName": "X-API-Key" } } } ] )

Add a Smithy target

Select one of the following methods:

AgentCore starter toolkit

The AgentCore starter toolkit lets you create a Smithy target with a default model definition in DynamoDB if you omit the targetConfiguration field. The following example shows the creation of the default Smithy model definition and also a custom one uploaded to S3.

from bedrock_agentcore_starter_toolkit.operations.gateway.client import GatewayClient # Initialize the Gateway client gateway_client = GatewayClient(region_name="us-west-2") # Create a Smithy model target for a built-in AWS service (this default configuration uses a DynamoDB Smithy model) smithy_target = gateway_client.create_mcp_gateway_target( gateway=gateway, target_type="smithyModel" ) # Or create a Smithy model target with a custom model custom_smithy_target = gateway_client.create_mcp_gateway_target( gateway=gateway, target_type="smithyModel", target_payload={ "s3": { "uri": "s3://your-bucket/path/to/smithy-model.json" } } )
Boto3

The following Python code shows how to add a Smithy model target using the AWS Python SDK (Boto3):

import boto3 # Create the agentcore client agentcore_client = boto3.client('bedrock-agentcore-control') # Create a Smithy model target target = agentcore_client.create_gateway_target( gatewayIdentifier="your-gateway-id", name="DynamoDBTarget", targetConfiguration={ "mcp": { "smithyModel": { "s3": { "uri": "s3://your-bucket/path/to/smithy-model.json", "bucketOwnerAccountId": "123456789012" } } } }, credentialProviderConfigurations=[ { "credentialProviderType": "GATEWAY_IAM_ROLE" } ] )

Add an MCP server target

You can add an MCP server target and synchronize targets using the CLI.

CLI

The AgentCore CLI provides a simple way to add MCP server targets:

# Create MCP server as target {gatewayUrl}/gateways/{gatewayIdentifier}/targets { "name": "myMCPTarget", "description": "description of my MCP target", "credentialProviderConfigurations": [{ "credentialProviderType": "OAUTH", "credentialProvider": { "oauthCredentialProvider": { "providerArn": "arn:aws:bedrock-agentcore:{region}:{account}:token-vault/default/oauth2credentialprovider/resource-provider-oauth-test", "scopes": [] } } }], "targetConfiguration": { "mcp": { "mcpServer": { "endpoint": "myMCPServerURL" } } } } # SynchronizeGatewayTargets {gatewayUrl}/gateways/{gatewayIdentifier}/synchronizeTargets { "targetIdList": [ "<targetId>" ] }