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列出 AgentCore 閘道中的可用提示 - Amazon Bedrock AgentCore
列出提示的程式碼範例

列出 AgentCore 閘道中的可用提示

若要列出 AgentCore 閘道提供的所有可用提示，請對閘道的 MCP 端點提出 POST 請求，並在請求內文中指定 prompts/list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 API 的回應所提供。

  • ${Authorization header} – 當您設定傳入授權時，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) 中的列出提示所指定。包含 prompts/list做為 method。

注意

如需 prompts/list 選用支援參數的清單，請參閱模型內容通訊協定文件 中提示 請求內文中的 params 物件。在搜尋列旁的頁面頂端，您可以選取要檢視其文件的 MCP 版本。請確定 Amazon Bedrock AgentCore 支援該版本。

回應會傳回可用提示清單，其中包含其名稱、描述和引數。

列出提示的程式碼範例

若要查看在閘道中列出可用提示的範例，請選取下列其中一種方法：

範例
Python requests package

  1. import requests
import json

def list_prompts(gateway_url, access_token):
    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {access_token}"
    }

    payload = {
        "jsonrpc": "2.0",
        "id": "list-prompts-request",
        "method": "prompts/list"
    }

    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
prompts = list_prompts(gateway_url, access_token)
print(json.dumps(prompts, indent=2))
MCP Client

  1. import asyncio
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client

async def execute_mcp(
    url,
    token,
    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. List available prompts
            print("Listing prompts...")
            cursor = True
            prompts = []
            while cursor:
                next_cursor = cursor
                if isinstance(cursor, bool):
                    next_cursor = None
                list_prompts_response = await session.list_prompts(next_cursor)
                prompts.extend(list_prompts_response.prompts)
                cursor = list_prompts_response.nextCursor

            prompt_names = []
            if prompts:
                for prompt in prompts:
                    prompt_names.append(prompt.name)
            prompt_names_string = "\n".join(prompt_names)
            print(
                f"List MCP prompts. # of prompts - {len(prompts)}\n"
                f"List of prompts - \n{prompt_names_string}\n"
            )

async def main():
    url = "https://${GatewayEndpoint}/mcp"
    token = "your_bearer_token_here"

    # Optional additional headers
    additional_headers = {
        "Content-Type": "application/json",
    }

    await execute_mcp(
        url=url,
        token=token,
        headers=additional_headers
    )

# Run the async function
if __name__ == "__main__":
    asyncio.run(main())
Strands MCP Client

  1. # NOTE: Strands SDK prompt support may vary. Use the MCP Client approach above
# for the most reliable prompts/list implementation.
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.list_prompts_sync()
        print(f"Found the following prompts: {[prompt.name for prompt in result.prompts]}")

run_agent(<MCP URL>, <Access token>)
LangGraph MCP Client

  1. # NOTE: LangGraph MCP adapter prompt support may vary. Use the MCP Client
# approach above for the most reliable prompts/list implementation.

import asyncio
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client

async def list_prompts(url, token):
    headers = {"Authorization": f"Bearer {token}"}
    async with streamablehttp_client(url=url, headers=headers) as (
        read_stream, write_stream, callA
    ):
        async with ClientSession(read_stream, write_stream) as session:
            await session.initialize()
            response = await session.list_prompts()
            for prompt in response.prompts:
                print(f"{prompt.name} - {prompt.description}")

asyncio.run(list_prompts("https://${GatewayEndpoint}/mcp", "${AccessToken}"))
注意

提示名稱的字首為目標名稱，格式為 {targetName}___{promptName}。這是用於工具的相同命名慣例。如需詳細資訊，請參閱工具命名慣例。

注意

如需使用提示編寫 MCP 伺服器的資訊，請參閱 MCP 狀態功能。