remio-mcp

# remio-mcp [](https://www.npmjs.com/package/remio-mcp) [](LICENSE) MCP (Model Context Protocol) server for [Remio](https://remio.ai) — expose your Remio knowledge base to AI agents like Claude, Cursor, and any MCP-compatible client. [中文文档](README.zh.md) ## Why MCP Instead of CLI? Remio already ships a CLI (`remio search_notes`, `remio rag`, etc.) that works great for manual use in the terminal. So why wrap it as an MCP server? **The CLI is built for humans. MCP is built for AI agents.** | | Remio CLI | remio-mcp | |---|---|---| | Usage | Manual commands in terminal | AI agent calls tools directly | | Integration | Shell scripts, task runners | Claude, Cursor, Craft Agents, any MCP client | | Structured output | `--json` flag required | Always structured, typed | | In Craft Agents | Requires a custom skill + Bash | Native source, works in Explore mode | | Discoverability | AI must guess command syntax | AI sees typed tool schemas | In tools like **Craft Agents**, the difference is especially clear: a CLI-based skill requires the agent to compose shell commands and parse raw output every time. An MCP source is a registered, always-available integration — the agent knows exactly what tools exist, what parameters they take, and can call them in Explore (read-only) mode without extra setup. In short: if you use Remio alongside AI agents, MCP gives you a cleaner, more reliable integration with zero friction. ## Prerequisites - [Remio desktop app](https://remio.ai) installed and running - Remio CLI installed (`remio` in your PATH, typically `~/.local/bin/remio`) - Node.js 18+ ## Installation Install via npm: ```bash npm install -g remio-mcp ``` Or use directly with npx (no install needed): ```bash npx remio-mcp ``` ## Setup ### Claude Desktop / Claude Code Add to your `claude_desktop_config.json`: ```json { "mcpServers": { "remio": { "command": "npx", "args": ["-y", "remio-mcp"], "env": { "REMIO_PATH": "/Users/YOUR_USERNAME/.local/bin/remio" } } } } ``` ### Craft Agents Add to your workspace source config (`~/.craft-agent/workspaces/my-workspace/sources/remio/config.json`): ```json { "name": "Remio", "slug": "remio", "type": "mcp", "mcp": { "transport": "stdio", "command": "npx", "args": ["-y", "remio-mcp"], "env": { "REMIO_PATH": "/Users/YOUR_USERNAME/.local/bin/remio" }, "authType": "none" } } ``` ## Available Tools | Tool | Description | |------|-------------| | `search_notes` | Search notes by query, type, date, people, or collection | | `read_note` | Read the full content of a note by ID | | `create_note` | Create a new note | | `update_note` | Update an existing note | | `delete_note` | Delete a note | | `add_note_to_collection` | Add a note to a collection | | `remove_note_from_collection` | Remove a note from a collection | | `create_people_note` | Create a contact/people note | | `rag` | Ask a question using RAG over your notes | ## Environment Variables | Variable | Default | Description | |----------|---------|-------------| | `REMIO_PATH` | `remio` | Path to the remio CLI binary | Find your remio CLI path with: `which remio` or `ls ~/.local/bin/remio` ## Usage Examples Once connected, you can ask your AI agent: - *"Search my Remio notes about design systems"* - *"What do my notes say about TypeScript best practices?"* (uses RAG) - *"Create a note titled 'Meeting with Alex' with these action items..."* - *"Find notes from last week about the product roadmap"* ## Development ```bash git clone https://github.com/GeekMai90/remio-mcp cd remio-mcp npm install npm run build ``` Test locally: ```bash REMIO_PATH=~/.local/bin/remio node dist/index.js ``` ## License MIT