AIML-MCP

AIML-MCP

The Model Context Protocol (MCP) is an open standard that enables AI systems– such as large language models (LLMs) — to securely connect with the tools and data sources organizations already use

1: Start the Server:
Make sure you have FastAPI and Uvicorn installed:

pip install fastapi uvicorn
Then, start the MCP server:

cd server
uvicorn main:app --reload
This starts a FastAPI server with:

POST /rpc: JSON-RPC handler for tool listing and invocation
GET /events: Simulated SSE endpoint emitting heartbeat messages every 5 seconds

2️: Run the Client:
Install the required Python requests package:

pip install requests
Then run the client to interact with the server:

cd client
python main.py
Output:

Tools: [{'name': 'greet', 'description': 'Greets the user', ...}]
Response: {'message': 'Hello, Sri!'}
You can run http://localhost:8000/events and you should see the heartbeat event being returned like the one shown below.

_data: {'event': 'heartbeat'}

data: {'event': 'heartbeat'} _ ...

What It Demonstrates:
A basic MCP server exposing tools via tools/list and tools/call
A client sending JSON-RPC requests to list and call tools
Simulated real-time connection using /events SSE endpoint
Modular structure ready to extend for resources/ and prompts/ support

Next Steps:
You can expand this prototype by:

Adding more tools with different schemas
Supporting resources/list and resources/read
Managing prompt templates with prompts/get
Implementing authentication and access control
Handling streaming responses from server to client

https://modelcontextprotocol.io/introduction
https://www.jsonrpc.org/specification
https://fastapi.tiangolo.com/
https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events

Code Source:

https://srivatssan.medium.com/model-context-protocol-exhaustively-explained-f5a30a87a3ff

https://github.com/srivatssan/MCP-Demo/blob/main/README.md