model-context-protocol

@PyBhagya

关于 model-context-protocol

A custom server project built using the Model Context Protocol (MCP) in Python. This repository documents my learning, experiments, and development progress.

#model-context-protocol #ai #note-taking

基本信息

分类

其他

许可证

Unlicense

运行时

python

传输方式

stdio

发布者

PyBhagya

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "model-context-protocol-pybhagya": {
      "command": "python",
      "args": [
        "main.py"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is model-context-protocol?

model-context-protocol is a Python MCP server that implements a simple AI Sticky Notes application. It demonstrates core Model Context Protocol concepts by providing tools, resources, and prompts for note management and AI summarization. It is intended for developers learning MCP or building note‑taking integrations with LLMs.

How to use model-context-protocol?

Run python main.py from the project root to start the server. The server exposes endpoints for adding notes (add_note tool), reading all notes (read_notes tool), accessing the latest note (notes://latest resource), and generating a prompt for note summarization (note_summary_prompt prompt). No additional configuration is required.

Key features of model-context-protocol

Persistent note storage using a file‑based backend
Add and retrieve notes via MCP tool endpoints
Resource endpoint for the most recent note
Prompt template for AI summarization of all notes
Built on the FastMCP server framework in Python

Use cases of model-context-protocol

Learning how to structure an MCP server with tools, resources, and prompts
Building a simple note‑taking API that can be consumed by AI models
Prototyping a backend for an AI‑assisted sticky notes application
Extending the server with new functionality like editing or deletion

FAQ from model-context-protocol

What does model-context-protocol do?

It is a demonstration MCP server that manages sticky notes (add, read, get latest) and provides a prompt to ask an AI to summarize them.

How do I run model-context-protocol?

Run python main.py in the project directory. The server will start using the FastMCP framework.

What dependencies are required?

The README only specifies Python and the MCP framework (FastMCP). Other dependencies are not listed.

What transport protocol does the server use?

The README does not specify the transport (e.g., stdio or HTTP). The default FastMCP transport is likely used but not documented here.

Can I use model-context-protocol with any LLM?

Yes, the server is designed to be connected to LLMs via MCP. The note_summary_prompt generates a prompt that can be sent to any compatible AI.

评论

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