# 在 AgentCore 閘道中呼叫工具
若要呼叫特定工具，請對閘道的 MCP 端點提出 POST 請求，並在請求內文、工具名稱和引數中指定 `tools/call`作為方法：
```
POST /mcp HTTP/1.1
Host: ${GatewayEndpoint}
Content-Type: application/json
Authorization: ${Authorization header}
${RequestBody}
```
取代以下的值：
+ `${GatewayEndpoint}` – 閘道的 URL，如 [CreateGateway](https://docs.aws.amazon.com/bedrock-agentcore-control/latest/APIReference/API_CreateGateway.html) API 的回應所提供。
+ `${Authorization header}` – 當您設定[傳入](gateway-inbound-auth.md)授權時，來自身分提供者的授權憑證。
+ `${RequestBody}` – 請求內文的 JSON 承載，如[模型內容通訊協定 (MCP)](https://modelcontextprotocol.io/docs/getting-started/intro) 中的[呼叫工具](https://modelcontextprotocol.io/specification/2025-06-18/server/tools#calling-tools)所指定。包含 `tools/call`做為 `method`，並包含 工具`name`的 及其 `arguments`。
回應會傳回工具傳回的內容和相關聯的中繼資料。
## 呼叫工具的程式碼範例
若要查看閘道中列出可用工具的範例，請選取下列其中一種方法：
**Example**
1. 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`。
```
curl -X POST \
https://mygateway-abcdefghij.gateway.bedrock-agentcore.us-west-2.amazonaws.com/mcp \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
-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
}
}
}
}'
```
1.
```
import requests
import json
def call_tool(gateway_url, access_token, tool_name, arguments):
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {access_token}"
}
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))
```
1.
```
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())
```
1. 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)
```
1. 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
```
## 錯誤
`tools/call` 操作可能會傳回下列類型的錯誤：
+ 在 HTTP 狀態碼中傳回的錯誤：
**AuthenticationError**
由於身分驗證登入資料無效，請求失敗。
**HTTP 狀態碼**：401
**AuthorizationError**
呼叫者沒有叫用工具的許可。
**HTTP 狀態碼**：403
**ResourceNotFoundError**
指定的工具不存在。
**HTTP 狀態碼**：404
**ValidationError**
提供的引數不符合工具的輸入結構描述。
**HTTP 狀態碼**：400
**ToolExecutionError**
執行工具時發生錯誤。
**HTTP 狀態碼**：500
**InternalServerError**
發生內部伺服器錯誤。
**HTTP 狀態碼**：500
+ MCP 錯誤。如需這些錯誤類型的詳細資訊，請參閱[模型內容通訊協定 (MCP)](https://modelcontextprotocol.io/docs/getting-started/intro) 文件中的[錯誤處理](https://modelcontextprotocol.io/specification/2024-11-05/server/tools#error-handlinghttps://modelcontextprotocol.io/specification/2024-11-05/server/tools#error-handling)。