# 在 AgentCore 网关中调用工具
要调用特定工具，请向网关的 MCP 端点发出 POST 请求，并在请求正文中指定该工具的名称和参数`tools/call`作为方法：
```
POST /mcp HTTP/1.1
Host: ${GatewayEndpoint}
Content-Type: application/json
Authorization: ${Authorization header}
${RequestBody}
```
替换以下值：
+ `${GatewayEndpoint}`— 网关的网址，如 [CreateGateway](https://docs.aws.amazon.com/bedrock-agentcore-control/latest/APIReference/API_CreateGateway.html)API的响应所示。
+ `${Authorization header}`— 设置[入站授权时身份提供商提供的授权凭证](gateway-inbound-auth.md)。
+ `${RequestBody}`— 请求正文的 JSON 有效负载，如[模型上下文协议 (MCP)](https://modelcontextprotocol.io/docs/getting-started/intro) 中的[调用工具](https://modelcontextprotocol.io/specification/2025-06-18/server/tools#calling-tools)中所述。包含`tools/call`为`method`并包括工具及其的`arguments`。`name`
响应返回工具返回的内容和关联的元数据。
## 调用工具的代码示例
要查看在网关中列出可用工具的示例，请选择以下方法之一：
**Example**
1. 以下 curl 请求显示了`searchProducts`通过网关调用 ID `mygateway-abcdefghij` 的工具的示例请求。
```
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：这是用于调用代理
```
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：这是用于调用代理
```
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
```
## 错误
该`tools/call`操作可能返回以下类型的错误：
+ 作为 HTTP 状态码的一部分返回的错误：
**AuthenticationError**
由于身份验证凭证无效，请求失败。
**HTTP 状态码**：401
**AuthorizationError**
调用者无权调用该工具。
**HTTP 状态码**：403
**ResourceNotFoundError**
指定的工具不存在。
**HTTP 状态码**：404
**ValidationError**
提供的参数不符合该工具的输入架构。
**HTTP 状态码**：400
**ToolExecutionError**
执行该工具时出错。
**HTTP 状态码**：500
**InternalServerError**
发生内部服务器错误。
**HTTP 状态码**：500
+ MCP 错误。有关这些类型的错误的更多信息，请参阅[模型上下文协议 (MCP)](https://modelcontextprotocol.io/docs/getting-started/intro) 文档中的[错误处理](https://modelcontextprotocol.io/specification/2024-11-05/server/tools#error-handlinghttps://modelcontextprotocol.io/specification/2024-11-05/server/tools#error-handling)。