- curl (2025-11-25 and earlier)
-
下列 curl 請求顯示透過 ID 為 searchProducts的閘道呼叫 工具的範例請求mygateway-abcdefghij。將 MCP-Protocol-Version標頭設定為閘道支援的版本。
curl -X POST \
https://mygateway-abcdefghij.gateway.bedrock-agentcore.us-west-2.amazonaws.com/mcp \
-H "Accept: application/json, text/event-stream" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
-H "MCP-Protocol-Version: 2025-11-25" \
-d '{
"jsonrpc": "2.0",
"id": "invoke-tool-request",
"method": "tools/call",
"params": {
"name": "searchProducts",
"arguments": {
"query": "wireless headphones",
"category": "Electronics",
"maxResults": 2,
"priceRange": {
"min": 50.00,
"max": 200.00
}
}
}
}'
- curl (2026-07-28)
-
在版本 上2026-07-28，在內文中包含 Mcp-Method和 Mcp-Name request-metadata 標頭和_meta版本欄位。MCP-Protocol-Version 標頭必須符合 _meta.io.modelcontextprotocol/protocolVersion。閘道的 supportedVersions 必須包含 2026-07-28。
curl -X POST \
https://mygateway-abcdefghij.gateway.bedrock-agentcore.us-west-2.amazonaws.com/mcp \
-H "Accept: application/json, text/event-stream" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
-H "MCP-Protocol-Version: 2026-07-28" \
-H "Mcp-Method: tools/call" \
-H "Mcp-Name: searchProducts" \
-d '{
"jsonrpc": "2.0",
"id": "invoke-tool-request",
"method": "tools/call",
"params": {
"name": "searchProducts",
"arguments": {
"query": "wireless headphones",
"category": "Electronics",
"maxResults": 2,
"priceRange": {
"min": 50.00,
"max": 200.00
}
},
"_meta": {
"io.modelcontextprotocol/protocolVersion": "2026-07-28",
"io.modelcontextprotocol/clientInfo": {
"name": "my-agent",
"version": "1.0.0"
},
"io.modelcontextprotocol/clientCapabilities": {}
}
}
}'
- Python requests package (2025-11-25 and earlier)
-
將 MCP-Protocol-Version標頭設定為閘道支援的版本。
import requests
import json
def call_tool(gateway_url, access_token, tool_name, arguments):
headers = {
"Accept": "application/json, text/event-stream",
"Content-Type": "application/json",
"Authorization": f"Bearer {access_token}",
"MCP-Protocol-Version": "2025-11-25"
}
payload = {
"jsonrpc": "2.0",
"id": "call-tool-request",
"method": "tools/call",
"params": {
"name": tool_name,
"arguments": arguments
}
}
response = requests.post(gateway_url, headers=headers, json=payload)
return response.json()
# Example usage
gateway_url = "https://${GatewayEndpoint}/mcp" # Replace with your actual gateway endpoint
access_token = "${AccessToken}" # Replace with your actual access token
result = call_tool(
gateway_url,
access_token,
"openapi-target-1___get_orders_byId", # Replace with <{TargetId}__{ToolName}>
{"orderId": "ORD-12345-67890", "customerId": "CUST-98765"}
)
print(json.dumps(result, indent=2))
- Python requests package (2026-07-28)
-
在版本 上2026-07-28，在內文中包含 Mcp-Method和 Mcp-Name request-metadata 標頭和_meta版本欄位。MCP-Protocol-Version 標頭必須符合 _meta.io.modelcontextprotocol/protocolVersion。閘道的 supportedVersions 必須包含 2026-07-28。
import requests
import json
def call_tool(gateway_url, access_token, tool_name, arguments):
headers = {
"Accept": "application/json, text/event-stream",
"Content-Type": "application/json",
"Authorization": f"Bearer {access_token}",
"MCP-Protocol-Version": "2026-07-28",
"Mcp-Method": "tools/call",
"Mcp-Name": tool_name
}
payload = {
"jsonrpc": "2.0",
"id": "call-tool-request",
"method": "tools/call",
"params": {
"name": tool_name,
"arguments": arguments,
"_meta": {
"io.modelcontextprotocol/protocolVersion": "2026-07-28",
"io.modelcontextprotocol/clientInfo": {"name": "my-agent", "version": "1.0.0"},
"io.modelcontextprotocol/clientCapabilities": {}
}
}
}
response = requests.post(gateway_url, headers=headers, json=payload)
return response.json()
# Example usage
gateway_url = "https://${GatewayEndpoint}/mcp" # Replace with your actual gateway endpoint
access_token = "${AccessToken}" # Replace with your actual access token
result = call_tool(
gateway_url,
access_token,
"openapi-target-1___get_orders_byId", # Replace with <{TargetId}__{ToolName}>
{"orderId": "ORD-12345-67890", "customerId": "CUST-98765"}
)
print(json.dumps(result, indent=2))
- MCP Client
-
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
import asyncio
async def execute_mcp(
url,
token,
tool_params,
headers=None
):
default_headers = {
"Authorization": f"Bearer {token}"
}
headers = {**default_headers, **(headers or {})}
async with streamablehttp_client(
url=url,
headers=headers,
) as (
read_stream,
write_stream,
callA,
):
async with ClientSession(read_stream, write_stream) as session:
# 1. Perform initialization handshake
print("Initializing MCP...")
_init_response = await session.initialize()
print(f"MCP Server Initialize successful! - {_init_response}")
# 2. Call specific tool
print(f"Calling tool: {tool_params['name']}")
tool_response = await session.call_tool(
name=tool_params['name'],
arguments=tool_params['arguments']
)
print(f"Tool response: {tool_response}")
return tool_response
async def main():
url = "https://${GatewayEndpoint}/mcp"
token = "your_bearer_token_here"
tool_params = {
"name": "LambdaTarget___get_order_tool",
"arguments": {
"orderId": "order123"
}
}
await execute_mcp(
url=url,
token=token,
tool_params=tool_params
)
if __name__ == "__main__":
asyncio.run(main())
- Strands MCP Client
-
注意：這是用於叫用 代理程式。
from strands.tools.mcp.mcp_client import MCPClient
from mcp.client.streamable_http import streamablehttp_client
def create_streamable_http_transport(mcp_url: str, access_token: str):
return streamablehttp_client(mcp_url, headers={"Authorization": f"Bearer {access_token}"})
def run_agent(mcp_url: str, access_token: str):
mcp_client = MCPClient(lambda: create_streamable_http_transport(mcp_url, access_token))
with mcp_client:
result = mcp_client.call_tool_sync(
tool_use_id="tool-123", # A unique ID for the tool call
name="openapi-target-1___get_orders", # The name of the tool to invoke
arguments={} # A dictionary of arguments for the tool
)
print(result)
url = {gatewayUrl}
token = {AccessToken}
run_agent(url, token)
- LangGraph MCP Client
-
注意：這是用於叫用 代理程式。
import asyncio
from langgraph.prebuilt import create_react_agent
def execute_agent(
user_prompt,
model_id,
region,
tools
):
model = ChatBedrock(model_id=model_id, region_name=region)
agent = create_react_agent(model, tools)
_response = asyncio.run(agent.ainvoke({
"messages": user_prompt
}))
_response = _response.get('messages', {})[1].content
print(
f"Invoke Langchain Agents Response"
f"Response - \n{_response}\n"
)
return _response
