Learn about Ming MCP Server for managing notes with core MCP features and TypeScript implementation
The Ming-MCP-Server is a TypeScript-based implementation of Model Context Protocol (MCP) that serves as an adapter for various AI applications. It demonstrates core MCP concepts by providing functionalities such as managing text notes, creating new notes, and generating summaries of those notes. This server acts like a bridge, allowing AI applications to interact with specific data sources or tools via a standardized protocol.
The Ming-MCP-Server supports several key features integral to MCP:
note://
URIs. Each note consists of metadata, such as a title and content.create_note
): This tool enables the creation of new notes by requiring title and content parameters, which then gets stored in the server's state.summarize_notes
): Generates a structured summary of all stored notes, with the summaries themselves included as embedded resources.The architecture of Ming-MCP-Server centers around two core components:
graph TD
A[AI Application] -->|MCP Client| B[MCP Protocol]
B --> C[MCP Server]
C --> D[Data Source/Tool]
style A fill:#e1f5fe
style C fill:#f3e5f5
style D fill:#e8f5e8
Below is a matrix detailing the compatibility of different MCP clients with this server:
MCP Client | Resources | Tools | Prompts | Status |
---|---|---|---|---|
Claude Desktop | ✅ | ✅ | ✅ | Full Support |
Continue | ✅ | ✅ | ✅ | Full Support |
Cursor | ❌ | ✅ | ❌ | Tools Only |
To get started, install the necessary dependencies:
npm install
Build the server to ensure it's ready for use:
npm run build
For real-time development with automatic rebuilding:
npm run watch
Imagine you’re developing a project management tool that requires users to input and manage notes in real-time. Using Ming-MCP-Server, your tool can seamlessly integrate with various AI applications such as Claude Desktop or Continue. The server maintains the state of all notes, ensuring they are accessible when needed.
In a collaborative writing project, multiple users contribute to a document that needs periodic summaries for easy reference. Ming-MCP-Server can be set up to generate these summaries automatically using prompts. This feature enhances productivity by ensuring everyone is always aware of the current state and context of the work.
To integrate with MCP clients like Claude Desktop or Continue, add the server configuration details in their respective settings. For example, on MacOS, you would update ~/Library/Application Support/Claude/claude_desktop_config.json
to:
{
"ming-mcp-server": {
"command": "node",
"args": [
"/private/tmp/ming-mcp-server/build/index.js",
"--api-key", "your-api-key"
]
}
}
Ming-MCP-Server is optimized for performance, ensuring minimal latency between the AI application and underlying resources. The compatibility matrix above provides a clear view of which clients are fully supported.
Additionally, the server supports the following protocol versions:
Protocol Version | Support Status |
---|---|
1.0 | ✅ |
1.1 | ✅ |
For advanced users, Ming-MCP-Server allows customization through environment variables and command-line arguments. To enhance security, consider setting up authentication mechanisms such as API keys.
{
"mcpServers": {
"[server-name]": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-[name]"],
"env": {
"API_KEY": "your-api-key"
}
}
}
}
Ming-MCP-Server enriches AI applications by providing a standardized interface for managing contextual data, enabling seamless integration with various tools and resources.
Claude Desktop and Continue have full support as demonstrated in the compatibility matrix. Other clients may require additional setup or configuration.
Currently, Cursor supports tool functionalities but does not integrate fully with notes and prompts.
It is recommended to manage your API keys securely by setting them as environment variables or using a secrets management service.
For handling large datasets, ensure your server can scale appropriately. Consider implementing caching mechanisms and optimizing data storage practices to maintain performance.
Contributions to Ming-MCP-Server are welcome! To get involved, follow these steps:
git clone https://github.com/[your-repo-url]
npm install
Join the broader MCP community by exploring additional resources such as the official documentation, forums, and third-party tools compatible with MCP. Together, we can build more robust and flexible AI applications.
By following this guide, developers can harness the power of MCP with Ming-MCP-Server to create sophisticated AI workflows that cater to a wide range of needs in the modern tech landscape.
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