Implementing a Custom Transport Layer in MCP

Abstract

The Model Context Protocol (MCP) is designed to be transport-agnostic. While most implementations support stdio and SSE by default, real-world enterprise systems often require custom transports such as:

• HTTP (JSON-RPC over POST)

• WebSocket (bidirectional streaming)

• Message queues (Kafka, RabbitMQ)

This article explains how MCP works internally and how to implement a custom transport layer (HTTP and WebSocket) in Python.

Understanding MCP Architecture

MCP separates two concerns:

Layer	Responsibility
Protocol Layer	JSON-RPC message format
Transport Layer	How messages are delivered

MCP defines:

• Tool registration

• JSON-RPC methods (tools/list, tools/call)

• Structured request/response format

It does not mandate how messages are transported. That’s why you can plug in custom transports.

MCP Internal Flow

Client - Transport Layer - MCP Message Handler - Tool Execution - Transport Response

The key idea:

Your custom transport only needs to forward JSON messages to the MCP handler.

Implementing HTTP Transport (JSON-RPC over POST)

This is ideal when:

• Integrating with API gateways

• Deploying in microservices

• Running behind load balancers

Install Dependencies

pip install fastapi uvicorn mcp

Example HTTP MCP Server

# http_mcp_server.py

from fastapi import FastAPI, Request
from mcp.server.fastmcp import FastMCP

app = FastAPI()
mcp = FastMCP("HTTP MCP Server")

# Define tool
@mcp.tool()
def leave_balance(employee_name: str) -> int:
    return {"Jayant": 15}.get(employee_name, 0)

@app.post("/mcp")
async def handle_mcp(request: Request):
    body = await request.json()
    # Pass raw JSON-RPC message to MCP
    response = await mcp.handle_message(body)
    return response

Run Server

uvicorn http_mcp_server:app --reload

Endpoint:

POST http://localhost:8000/mcp

Characteristics of HTTP Transport

• Stateless

• Simple to deploy

• No streaming support (unless chunked)

• Easy to secure via middleware

Implementing WebSocket Transport

WebSocket is ideal for:

• Streaming LLM responses

• Real-time agents

• Long-lived sessions

WebSocket MCP Server

# websocket_mcp_server.py

from fastapi import FastAPI, WebSocket
from mcp.server.fastmcp import FastMCP
import json

app = FastAPI()
mcp = FastMCP("WebSocket MCP Server")

@mcp.tool()
def leave_balance(employee_name: str) -> int:
    return {"Jayant": 15}.get(employee_name, 0)

@app.websocket("/ws")
async def websocket_endpoint(websocket: WebSocket):
    await websocket.accept()
    while True:
        data = await websocket.receive_text()
        message = json.loads(data)
        response = await mcp.handle_message(message)
        await websocket.send_text(json.dumps(response))

Run Server

uvicorn websocket_mcp_server:app --reload

WebSocket endpoint:

ws://localhost:8000/ws

Supporting Streaming Responses

If your MCP server supports streaming tokens:

• HTTP - requires chunked responses

• WebSocket - naturally supports streaming

• SSE - designed for streaming

Transport Comparison

Transport	Streaming	Stateful	Best Use
stdio	Yes	Local only	Dev testing
SSE	Yes	Semi	Browser streaming
HTTP POST	No	Stateless	APIs
WebSocket	Yes	Yes	Agents, real-time

Conclusion

MCP is protocol-focused, not transport-bound.

To implement a custom transport:

1. Accept JSON-RPC message

2. Forward to handle_message()

3. Return response

4. Keep transport layer separate

By implementing HTTP or WebSocket adapters, you gain:

• Flexibility

• Scalability

• Enterprise readiness

• Real-time capability

Custom transport is not about changing MCP — it’s about extending infrastructure around it.