Notes MCP Server
The Notes MCP Server is a simple note storage system that allows you to:
Store notes: Add new notes using the
add-notetool by providing anameandcontentAccess notes: Retrieve individual notes via the custom
note://URI scheme, each with a name, description, andtext/plainmimetypeSummarize notes: Generate summaries of all stored notes using the
summarize-notesprompt, with an optionalstyleargument to control detail level (brief/detailed)
Allows publishing the MCP server package to PyPI for distribution
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Notes MCP Serversummarize my notes with detailed style"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
mcp-server-on-raspi MCP server
A MCP server project
Components
Resources
The server implements a simple note storage system with:
Custom note:// URI scheme for accessing individual notes
Each note resource has a name, description and text/plain mimetype
Prompts
The server provides a single prompt:
summarize-notes: Creates summaries of all stored notes
Optional "style" argument to control detail level (brief/detailed)
Generates prompt combining all current notes with style preference
Tools
The server implements one tool:
add-note: Adds a new note to the server
Takes "name" and "content" as required string arguments
Updates server state and notifies clients of resource changes
Related MCP server: mcp-meituan-ip
Configuration
[TODO: Add configuration details specific to your implementation]
Quickstart
Install
Claude Desktop
On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
Development
Building and Publishing
To prepare the package for distribution:
Sync dependencies and update lockfile:
uv syncBuild package distributions:
uv buildThis will create source and wheel distributions in the dist/ directory.
Publish to PyPI:
uv publishNote: You'll need to set PyPI credentials via environment variables or command flags:
Token:
--tokenorUV_PUBLISH_TOKENOr username/password:
--username/UV_PUBLISH_USERNAMEand--password/UV_PUBLISH_PASSWORD
Debugging
Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.
You can launch the MCP Inspector via npm with this command:
npx @modelcontextprotocol/inspector uv --directory /Users/daikiwatanabe/ghq/github.com/daikw/mcp-server-on-raspi run mcp-server-on-raspiUpon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
Available Tools
1 tooladd-noteC
Add a new note
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | ||
| name | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'Add a new note' and provides no details on side effects, permissions, return values, or error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence with no wasted words, making it concise and front-loaded. However, it is under-specified for the tool's complexity, though this is largely a completeness issue rather than a conciseness issue.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, output schema, and parameter descriptions, a five-word description is insufficient for an agent to invoke the tool correctly. The meaning of the parameters and expected return behavior remain ambiguous.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero description coverage for the two required parameters ('name' and 'content'), and the description does not explain their meaning or format. The agent cannot infer what 'name' or 'content' represent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Add') and a specific resource ('note'), clearly stating the tool's function. It differentiates itself from the sibling 'get_report', which is a read operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description only states the action without any context about when to invoke it or when to choose a sibling tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v1.0.0- First observed
add-note
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'add-note' has a clear and distinct purpose that cannot be confused with any other tool in this set.
The naming follows a consistent verb-noun pattern with 'add-note', and since there is only one tool, there is no inconsistency to evaluate. The naming is clear and predictable within this minimal set.
A single tool is too few for a server named 'Notes MCP Server', which implies a broader scope for managing notes (e.g., creating, reading, updating, deleting). This minimal set feels incomplete and under-scoped for the apparent domain.
The tool surface is severely incomplete for a notes management server. It only provides an 'add-note' tool, lacking essential operations like retrieving, updating, deleting, or listing notes, which will cause significant agent failures in typical workflows.
Maintenance
Related MCP Connectors
- TaprootOAuthcom.taproothq
Persistent memory layer for AI tools. Save and recall notes across Claude and other MCP clients.
Search, read, create and edit your Memol notes from Claude. Team note-taking with AI search.
Cross-session, cross-device memory for your agent: remember and recall notes. No key to start.
Google Keep-style notes app with an MCP server for AI agents to read/write notes.
Related MCP Servers
- FlicenseNot gradedqualityDmaintenanceA Claude-compatible MCP server that enables storing and summarizing notes through a simple note storage system with custom URI scheme.5-
- AlicenseBqualityDmaintenanceA simple note storage system that allows creating, storing, and summarizing notes with customizable detail levels.2MIT
- FlicenseBqualityDmaintenanceA simple system that allows Claude to leave and manage notes for itself across sessions, functioning like an 'Alexa, remind me...' for AI assistants.72-
- FlicenseBqualityDmaintenanceA simple notes system that allows creating, storing, and accessing text notes through MCP resources and tools, with prompt support for generating summaries of all stored notes.118 npm-