state-server
by norisuke3
A TypeScript-based MCP server that implements a simple notes system. It demonstrates core MCP concepts by providing resources, tools, and prompts for interacting with notes.
Last updated: N/A
What is state-server?
This is a Model Context Protocol (MCP) server built with TypeScript that provides a simple notes system. It allows you to create, store, and summarize text notes using resources, tools, and prompts.
How to use state-server?
To use this server with Claude Desktop, add the provided server configuration to your claude_desktop_config.json file, specifying the path to the built index.js file. You can then interact with the server through Claude Desktop. For debugging, use the MCP Inspector.
Key features of state-server
List and access notes via
note://URIsCreate new text notes with titles and content using the
create_notetoolGenerate summaries of all stored notes using the
summarize_notespromptPlain text mime type for simple content access
Use cases of state-server
Creating and managing personal notes within Claude Desktop
Summarizing collections of notes using LLMs
Demonstrating core MCP concepts
Integrating with other MCP-compatible applications
FAQ from state-server
How do I install the server?
How do I install the server?
Install dependencies using npm install, then build the server using npm run build.
How do I configure the server for Claude Desktop?
How do I configure the server for Claude Desktop?
Add the provided JSON configuration to your claude_desktop_config.json file, specifying the path to the built index.js file.
How do I debug the server?
How do I debug the server?
Use the MCP Inspector by running npm run inspector. It will provide a URL to access debugging tools in your browser.
What are the required parameters for creating a note?
What are the required parameters for creating a note?
The create_note tool requires title and content parameters.
What does the summarize_notes prompt do?
What does the summarize_notes prompt do?
It generates a summary of all stored notes, including all note contents as embedded resources, and returns a structured prompt for LLM summarization.