AIML-MCP
このプロジェクトはPythonを使用したAIおよび機械学習の基礎を学ぶためのものであり、初心者向けのリソースを提供します。機械学習の基本的な概念を理解し、簡単なモデルを構築するための手順が含まれています。
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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