About xNotepad AI
xNotepad AI is an MCP server that gives AI agents persistent, encrypted notes with search and question answering. It supports organizing and linking notebook content, with agent changes limited to agent-created notes.
Key features
- 01Create, read, and update notes
- 02Search notes semantically
- 03Ask questions about note content
- 04Tag, link, merge, and archive notes
- 05View note version history
Use cases
- 01Retain research and decisions between agent sessions
- 02Find earlier decisions using natural-language queries
- 03Organize notes with tags and wiki-links
- 04Share notebook memory across agents
MCP support
It exposes 13 note-management and retrieval tools over Streamable HTTP JSON-RPC at `https://www.xnotepadai.com/api/mcp/`, with bearer-token authentication.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://www.xnotepadai.com/api/mcp/claude mcp add --transport http com-xnotepadai-notes https://www.xnotepadai.com/api/mcp/{"mcpServers":{"com-xnotepadai-notes":{"type":"http","url":"https://www.xnotepadai.com/api/mcp/"}}}Open in Cursor{"servers":{"com-xnotepadai-notes":{"type":"http","url":"https://www.xnotepadai.com/api/mcp/"}}}Open in VS Code{"mcpServers":{"com-xnotepadai-notes":{"type":"http","url":"https://www.xnotepadai.com/api/mcp/"}}}{"mcpServers":{"com-xnotepadai-notes":{"serverUrl":"https://www.xnotepadai.com/api/mcp/"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
https://www.xnotepadai.com/api/mcp/Auth requiredTools
Details
From the project READMExNotePadAI — MCP Server
A 13-tool MCP server that gives AI agents persistent, encrypted, searchable memory via notes.
Endpoint: https://www.xnotepadai.com/api/mcp/
Protocol: MCP (Model Context Protocol) JSON-RPC over Streamable HTTP
Auth: Bearer token
Free tier: 1,000 calls/month
Quick Start
{
"mcpServers": {
"xnotepad": {
"type": "http",
"url": "https://www.xnotepadai.com/api/mcp/",
"headers": {
"Authorization": "Bearer YOUR_TOKEN_HERE"
}
}
}
}
Get your token: https://www.xnotepadai.com/settings/ → Your MCP Token (pre-generated, ready to copy)
Tools
| Tool | Description |
|---|---|
create_note | Create a note (auto-tagged agent-created) |
list_notes | List all notes with titles, sizes, dates |
get_note | Get full note content by ID |
update_note | Update content (agent-created notes only) |
delete_note | Delete a note (agent-created only) |
search_notes | Semantic search via vector embeddings |
ask_notes | Ask a question — AI answers from note content |
get_versions | Get version history for a note |
tag_note | Add tags to a note |
link_notes | Add [[wiki-links]] between notes |
merge_notes | Merge two notes (source deleted after) |
archive_note | Archive a note |
index_notes | Vectorise notes for semantic search |
Security Model
- Bearer token auth — SHA-256 hashed, stored in D1, revocable
- Tenant isolation — tenant ID derived from token lookup, never from client args
- Agent sandboxing — agents can only modify/delete notes tagged
agent-created - Rate limiting — 30 req/min per IP
- Zero-knowledge encryption — notes encrypted client-side with AES-256-GCM (MCP accesses unencrypted copies synced by the user)
Use Cases
- AI memory — agents save research, decisions, architecture notes between sessions
- Knowledge retrieval — "What did I decide about auth?" → searches your notes
- Note automation — auto-tag, auto-link, merge duplicates, archive old notes
- Multi-agent workflows — one agent writes, another reads later
Stack
- Cloudflare Workers (runtime)
- Cloudflare D1 (database)
- Cloudflare Vectorize (semantic search)
- Workers AI / Llama 3.3 70B (AI answers)
Docs
- MCP Integration: https://www.xnotepadai.com/mcp/
- API Reference: https://www.xnotepadai.com/developers/
- Privacy: https://www.xnotepadai.com/privacy/
License
MIT
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.