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列出 AgentCore 网关中的可用提示 - Amazon Bedrock AgentCore

列出 AgentCore 网关中的可用提示

要列出 AgentCore 网关提供的所有可用提示,请向网关的 MCP 端点发出 POST 请求,并在请求正文中指定prompts/list为方法:

POST /mcp HTTP/1.1 Host: ${GatewayEndpoint} Content-Type: application/json Authorization: ${Authorization header} ${RequestBody}

替换以下值:

注意

有关可选支持的参数列表prompts/list,请参阅模型上下文协议文档中的提示中请求正文中的params对象。在页面顶部搜索栏旁边,您可以选择要查看其文档的 MCP 版本。确保该版本是 Amazon Bedrock AgentCore 支持的版本。

响应会返回可用提示的列表,以及它们的名称、描述和参数。

列出提示的代码示例

要查看在网关中列出可用提示的示例,请选择以下方法之一:

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

使用以下格式{targetName}___{promptName},提示名称以目标名称为前缀。这与用于工具的命名约定相同。有关更多信息,请参阅工具命名约定

注意

有关使用提示创作 MCP 服务器的信息,请参阅 MCP 状态功能。