Répertorier les outils disponibles dans une AgentCore passerelle
Pour répertorier tous les outils disponibles fournis par une AgentCore passerelle, envoyez une requête POST au point de terminaison MCP de la passerelle et spécifiez tools/list comme méthode dans le corps de la demande :
POST /mcp HTTP/1.1
Host: ${GatewayEndpoint}
Content-Type: application/json
Authorization: ${Authorization header}
${RequestBody}
Remplacez les valeurs suivantes :
-
${GatewayEndpoint}— L'URL de la passerelle, telle que fournie dans la réponse de l'CreateGatewayAPI.
-
${Authorization header}— Les informations d'autorisation fournies par le fournisseur d'identité lorsque vous configurez l'autorisation entrante.
-
${RequestBody}— La charge utile JSON du corps de la requête, telle que spécifiée dans les outils de listage du Model Context Protocol (MCP). Inclure tools/list en tant quemethod.
La réponse renvoie une liste des outils disponibles avec leurs noms, leurs descriptions et leurs schémas de paramètres.
Exemples de code pour les outils de création de listes
Pour voir des exemples de liste des outils disponibles dans la passerelle, sélectionnez l'une des méthodes suivantes :
Exemple
- Python requests package
-
-
import requests
import json
def list_tools(gateway_url, access_token):
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {access_token}"
}
payload = {
"jsonrpc": "2.0",
"id": "list-tools-request",
"method": "tools/list"
}
response = requests.post(gateway_url, headers=headers, json=payload)
return response.json()
# Example usage
gateway_url = "https://${GatewayEndpoint}/mcp" # Replace with your actual gateway endpoint
access_token = "${AccessToken}" # Replace with your actual access token
tools = list_tools(gateway_url, access_token)
print(json.dumps(tools, indent=2))
- MCP Client
-
-
import asyncio
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
async def execute_mcp(
url,
token,
headers=None
):
default_headers = {
"Authorization": f"Bearer {token}"
}
headers = {**default_headers, **(headers or {})}
async with streamablehttp_client(
url=url,
headers=headers,
) as (
read_stream,
write_stream,
callA,
):
async with ClientSession(read_stream, write_stream) as session:
# 1. Perform initialization handshake
print("Initializing MCP...")
_init_response = await session.initialize()
print(f"MCP Server Initialize successful! - {_init_response}")
# 2. List available tools
print("Listing tools...")
cursor = True
tools = []
while cursor:
next_cursor = cursor
if type(cursor) == bool:
next_cursor = None
list_tools_response = await session.list_tools(next_cursor)
tools.extend(list_tools_response.tools)
cursor = list_tools_response.nextCursor
tool_names = []
if tools:
for tool in tools:
tool_names.append(tool.name)
tool_names_string = "\n".join(tool_names)
print(
f"List MCP tools. # of tools - {len(tools)}"
f"List of tools - \n{tool_names_string}\n"
)
async def main():
url = "https://${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
-
-
from strands.tools.mcp.mcp_client import MCPClient
from mcp.client.streamable_http import streamablehttp_client
import os
def create_streamable_http_transport(mcp_url: str, access_token: str):
return streamablehttp_client(mcp_url, headers={"Authorization": f"Bearer {access_token}"})
def get_full_tools_list(client):
"""
List tools w/ support for pagination
"""
more_tools = True
tools = []
pagination_token = None
while more_tools:
tmp_tools = client.list_tools_sync(pagination_token=pagination_token)
tools.extend(tmp_tools)
if tmp_tools.pagination_token is None:
more_tools = False
else:
more_tools = True
pagination_token = tmp_tools.pagination_token
return tools
def run_agent(mcp_url: str, access_token: str):
mcp_client = MCPClient(lambda: create_streamable_http_transport(mcp_url, access_token))
with mcp_client:
tools = get_full_tools_list(mcp_client)
print(f"Found the following tools: {[tool.tool_name for tool in tools]}")
run_agent(<MCP URL>, <Access token>)
- LangGraph MCP Client
-
-
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
def list_tools(
url,
headers
):
mcp_client = MultiServerMCPClient(
{
"agent": {
"transport": "streamable_http",
"url": url,
"headers": headers,
}
}
)
tools = asyncio.run(mcp_client.get_tools())
tool_details = []
tool_names = []
for tool in tools:
tool_names.append(f"{tool.name}")
tool_detail = f"{tool.name} - {tool.description} \n"
tool_properties = tool.args_schema.get('properties', {})
properties = []
for property_name, tool_property in tool_properties.items():
properties.append(f"{property_name} - {tool_property.get('description', None)} \n")
tool_details.append(f"{tool_detail}{"\n".join(properties)}")
tool_details_string = "\n".join(tool_details)
tool_names_string = "\n".join(tool_names)
print(
f"Langchain: List MCP tools. # of tools - {len(tools)}\n",
f"Langchain: List of tool names - \n{tool_names_string}\n"
f"Langchain: Details of tools - \n{tool_details_string}\n"
)
Si la recherche est activée sur la passerelle, l'outil de recherche x_amz_bedrock_agentcore_search sera répertorié en premier dans la réponse.