Why Streamable HTTP Is Replacing SSE in the MCP Protocol for AI Communication

MCP Overview

The Model Context Protocol (MCP) is an open standard driven by Anthropic that defines a bidirectional communication layer between large language models (LLMs) and external data sources or tools. Its core components are the MCP client (running on the LLM side), the MCP server (hosting the data source), and a context‑exchange protocol.

Limitations of Server‑Sent Events (SSE)

One‑way communication : SSE only pushes data from server to client, preventing true bidirectional interaction.

No built‑in session management : State must be tracked manually across requests.

Weak reconnection handling : Network interruptions can cause data loss.

UTF‑8 text only : Binary or structured payloads are not supported.

Streamable HTTP transport (recommended by MCP)

Single endpoint : All MCP traffic uses one HTTP path, simplifying network topology.

Multiple response modes : Supports JSON batch responses and SSE‑style streaming.

Built‑in session management : Uses the Mcp-Session-Id header to maintain context.

Connection recoverability : Reconnects without losing in‑flight data.

Flexible authentication : Works with various auth schemes.

CORS configuration : Allows fine‑grained cross‑origin settings for web clients.

Technical comparison

Communication direction : SSE – server → client only; Streamable HTTP – client ↔ server.

Session management : SSE – none; Streamable HTTP – Mcp-Session-Id header.

Data format support : SSE – UTF‑8 text; Streamable HTTP – JSON, binary, and other formats.

Auto‑reconnect : Both support it, but Streamable HTTP preserves data.

Infrastructure compatibility : Both have high compatibility with existing HTTP stacks.

Implementing an MCP server with Streamable HTTP

Starting from an SSE‑based weather‑query server, the only change is to set the transport to streamable-http when invoking FastMCP:

mcp = FastMCP(
    name="weather",
    host="0.0.0.0",
    port=8002,
    description="Get weather by city name or coordinates",
    sse_path="/mcp"
)

if __name__ == "__main__":
    print("Starting server...")
    mcp.run(transport='streamable-http')

After upgrading the mcp[cli] package to version 1.8.0, the server is reachable at http://127.0.0.1:8002/mcp.

Testing with Cherry Studio

Because the current Cursor tool does not yet support Streamable HTTP, the author uses Cherry Studio (downloadable from https://www.cherry-ai.com/) to configure and test the server. The workflow is:

Add a new MCP server in the UI.

Enter the server URL (e.g., http://127.0.0.1:8002/mcp).

Save the configuration.

Run concurrent queries such as weather for Beijing and Wuhan; the UI shows that Beijing returns first, confirming correct concurrency handling.

Implementing an MCP client for Streamable HTTP

The client mirrors the previous SSE implementation but adds a method that creates a Streamable HTTP transport and a ClientSession for tool calls:

async def connect_to_streamable_http_server(self, mcp_name, server_url: str):
    stdio_transport = await self.exit_stack.enter_async_context(
        streamablehttp_client(server_url)
    )
    self.streamable_http, self.write, _ = stdio_transport
    self.session = await self.exit_stack.enter_async_context(
        ClientSession(self.streamable_http, self.write)
    )
    self.sessions[mcp_name] = self.session
    await self.session.initialize()

Tool configuration is stored in a JSON file ( mcp.json). Example for a single weather server:

{
  "mcpServers": {
    "weather-http": {
      "isActive": true,
      "type": "streamable_http",
      "url": "http://127.0.0.1:8002/mcp",
      "name": "weather-http"
    }
  }
}

Example for multiple servers (weather and time):

{
  "mcpServers": {
    "time-http": {
      "isActive": true,
      "type": "streamable_http",
      "url": "https://time.mcp.minglog.cn/mcp",
      "name": "time-http"
    },
    "weather-http": {
      "isActive": true,
      "type": "streamable_http",
      "url": "http://127.0.0.1:8002/mcp",
      "name": "weather-http"
    }
  }
}

Full end‑to‑end demo

The client runs an interactive chat loop. A user can ask, for example, “What’s the weather in Wuhan and Beijing?”. The client sends the request to the appropriate MCP server via Streamable HTTP, receives tool results, and prints them. Screenshots in the original article show successful tool invocation and correct handling of concurrent requests.

Conclusion

Streamable HTTP combines the broad compatibility of standard HTTP with the real‑time push capabilities of SSE, while adding bidirectional communication, session management, and support for diverse data formats. These properties make it a strong candidate for the next‑generation transport layer in AI‑to‑application communication.