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mcp-server-sse

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Creates and configures HTTP with Server-Sent Events Model Context Protocol (MCP) server connections for OpenAI Agents SDK

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HTTP with SSE MCP Server Skill

This skill helps create and configure HTTP with Server-Sent Events Model Context Protocol (MCP) server connections for OpenAI Agents SDK.

Purpose

  • Create MCPServerSse configurations
  • Configure SSE connection parameters and headers
  • Connect to servers that implement HTTP with Server-Sent Events
  • Use SSE transport for MCP server communication

MCPServerSse Constructor Parameters

  • params (MCPServerSseParams): Connection parameters for the server
    • url (str): SSE endpoint URL for the MCP server
    • headers (dict[str, str], optional): HTTP headers to include with requests
    • timeout (timedelta | float, optional): The timeout for the HTTP request (default: 5 seconds)
    • sse_read_timeout (timedelta | float, optional): The timeout for the SSE connection (default: 5 minutes)
    • httpx_client_factory (HttpClientFactory, optional): Custom HTTP client factory for configuring httpx.AsyncClient behavior
  • cache_tools_list (bool): Whether to cache the list of available tools (default: False)
  • name (string | None): A readable name for the server (default: None, auto-generated from URL)
  • tool_filter (ToolFilter): The tool filter to use for filtering tools (default: None)
  • use_structured_content (bool): Whether to use tool_result.structured_content when calling an MCP tool (default: False)
  • max_retry_attempts (int): Number of times to retry failed list_tools/call_tool calls (default: 0)
  • retry_backoff_seconds_base (float): The base delay, in seconds, for exponential backoff between retries (default: 1.0)
  • message_handler (MessageHandlerFnT | None): Optional handler invoked for session messages (default: None)

Usage Context

Use this skill when:

  • Working with servers that implement HTTP with Server-Sent Events transport
  • Needing real-time event streaming from the MCP server
  • Using SSE-based MCP server implementations

Basic Example

import asyncio
from agents import Agent, Runner
from agents.model_settings import ModelSettings
from agents.mcp import MCPServerSse

workspace_id = "demo-workspace"

async def main() -> None:
    async with MCPServerSse(
        name="SSE Python Server",
        params={
            "url": "http://localhost:8000/sse",
            "headers": {"X-Workspace": workspace_id},
        },
        cache_tools_list=True,
    ) as server:
        agent = Agent(
            name="Assistant",
            mcp_servers=[server],
            model_settings=ModelSettings(tool_choice="required"),
        )
        result = await Runner.run(agent, "What's the weather in Tokyo?")
        print(result.final_output)

asyncio.run(main())