MCP Server

 
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent

client = MultiServerMCPClient(
    {
        "weather": {
            "transport": "streamable_http",
            "url": "https://api.distribusion.com/mcp/",
            "headers": {
                "api-key": "<RAPI_MCP_API_KEY>"
            },
        }
    }
)
tools = await client.get_tools()
agent = create_react_agent("openai:gpt-4.1", tools)
response = await agent.ainvoke({"messages": "london to paris tonight"})

 
import os

from google.adk.agents.llm_agent import Agent
from google.adk.tools.mcp_tool.mcp_session_manager import StreamableHTTPConnectionParams
from google.adk.tools.mcp_tool.mcp_toolset import MCPToolset


root_agent = Agent(
    name="retailer_agent",
    description="An agent that searches for ground transportation trips",
    model="gemini-2.5-flash",
    instruction="""
        Help the user find ground transportation trips.
        Follow this flow:
        1. Search for locations codes (using search_stations, search_areas, search_cities)
        2. Search for trips using those location codes and a certain departure date and time using connections_find
        3. Present the results to the user
        4. Based on the user's selection:
            4.1. Check the availability of the trip using connections_vacancy
            4.2. If the trip is available:
                4.2.1. Get the seat map (if available) for the trip and ask the user for a seat selection using get_seat_map
                4.2.2. Use the get_checkout_link tool to create a checkout link for the trip and present it to the user

        You may use the tools available to answer additional questions.""",
    tools=[
        MCPToolset(
            connection_params=StreamableHTTPConnectionParams(
                url="https://api.distribusion.com/mcp/",
                headers={"api-key": os.getenv("DISTRIBUSION_MCP_API_KEY", "")},
            )
        ),
    ],
)