Tome

What is Tome about?

Tome offers a beginner‑friendly desktop application that connects to any LLM—whether hosted locally via Ollama, LM Studio, etc., or remotely via Gemini, OpenAI, or compatible APIs—and augments the model with Model Context Protocol (MCP) servers for tool use, file access, and more.

How to use Tome?

1. Download & install the Windows or macOS installer from the latest GitHub release.
2. Add an LLM provider – preset options include Ollama, Gemini, and OpenAI; custom providers can be added by entering the API endpoint URL.
3. Install MCP servers via the MCP tab (e.g., paste uvx mcp-server-fetch or use the one‑click registry from Smithery.ai).
4. Chat or schedule prompts – start a conversation, or create hourly/daily tasks that run automatically.

Key Features of Tome

• Streamlined UI requiring no JSON, Docker, or command‑line configuration.
• Support for remote and local LLMs (Gemini, OpenAI, Ollama, LM Studio, Cortex, etc.).
• Scheduled tasks with flexible timing (hourly or daily).
• Integrated MCP server management (install, remove, toggle on/off) with support for npm, uvx, node, python servers.
• One‑click access to thousands of MCP servers via the Smithery.ai registry.
• Customizable context window size and temperature settings.
• Native handling of tool calls and reasoning model messages.

Use Cases of Tome

• Personal AI assistant – manage daily reminders, fetch news, summarize documents.
• Developer prototyping – quickly test LLM prompts with tool integration without writing code.
• Local‑first privacy – run Ollama/Qwen3 models with local MCP servers for private data handling.
• Education & experimentation – let non‑technical users explore LLM capabilities and tool usage.
• Automation – schedule recurring data‑fetching or reporting tasks powered by LLM reasoning.

FAQ from Tome

• Do I need to install Docker or Python? No. Tome runs as a native desktop app; MCP servers can be installed via simple commands or the built‑in registry.
• Is Linux supported? Currently macOS and Windows are supported; Linux is planned for a future release.
• Can I use my own MCP server? Yes, add the server’s command or URL in the MCP tab and toggle it on.
• What models are compatible? Any model exposing an OpenAI‑compatible API, including Ollama, Gemini, OpenAI, LM Studio, Cortex, and others.
• Is my data private? Tome is local‑first; data stays on your machine unless you connect to remote services.

Tome - Magical AI Spellbook

Tome

Tome is a desktop app that lets anyone harness the magic of LLMs and MCP. Download Tome, connect any local or remote LLM and hook it up to thousands of MCP servers to create your own magical AI-powered spellbook.

What is MCP? MCP stands for Model Context Protocol and lets your LLM access tools - like search engines, your filesystem, or APIs like Scryfall or Atlassian

🫥 Want it to be 100% local, 100% private? Use Ollama and Qwen3 with only local MCP servers to cast spells in your own pocket universe. ⚡ Want state of the art cloud models with the latest remote MCP servers? You can have that too. It's all up to you!

🏗️ This is a Technical Preview so bear in mind things will be rough around the edges. Join us on Discord to share tips, tricks, and issues you run into. Star this repo to stay on top of updates and feature releases!

🪄 Features

• 🧙 Streamlined Beginner Friendly Experience
  • Simply download and install Tome and hook up the LLM of your choice
  • No fiddling with JSON, Docker, python or node
  • Chat with MCP-powered models within minutes
• 🗓 NEW! Scheduled Tasks
  • Schedule prompts to run hourly or at a specific time every day
  • Support for any model or MCP servers
• 🤖 AI Model Support
  • Remote: Google Gemini, OpenAI, any OpenAI API-compatible endpoint
  • Local: Ollama, LM Studio, Cortex, any OpenAI API-compatible endpoint
• 🔮 Enhanced MCP support
  • UI to install, remove, turn on/off MCP servers
  • npm, uvx, node, python MCP servers all supported out of box
• 🏪 Integration into Smithery.ai registry
  • Thousands of MCP servers available via one-click installation
• ✏️ Customization of context windows and temperature
• 🧰 Native support for tool calls and reasoning models
  • UI enhancements that clearly delineate tool calls and thinking messages

Demo

https://github.com/user-attachments/assets/0775d100-3eba-4219-9e2f-360a01f28cce

Getting Started

Requirements

• MacOS or Windows (Linux coming soon!)
• LLM Provider of your choice: Ollama or Gemini API key are easy/free
• Download the latest release of Tome

Quickstart

1. Install Tome
2. Connect your preferred LLM provider - OpenAI, Ollama and Gemini are preset but you can also add providers like LM Studio by using http://localhost:1234/v1 as the URL
3. Open the MCP tab in Tome and install your first MCP server (Fetch is an easy one to get started with, just paste uvx mcp-server-fetch into the server field).
4. Chat with your MCP-powered model! Ask it to fetch the top story on Hacker News.

Vision

We want to make local LLMs and MCP accessible to everyone. We're building a tool that allows you to be creative with LLMs, regardless of whether you're an engineer, tinkerer, hobbyist, or anyone in between.

Core Principles

• Tome is local first: You are in control of where your data goes.
• Tome is for everyone: You shouldn't have to manage programming languages, package managers, or json config files.

What's Next

We've gotten a lot of amazing feedback in the last few weeks since releasing Tome but we've got big plans for the future. We want to break LLMs out of their chatbox, and we've got a lot of features coming to help y'all do that.

• Scheduled tasks: LLMs should be doing helpful things even when you're not in front of the computer.
• Native integrations: MCP servers are a great way to access tools and information, but we want to add more powerful integrations to interact with LLMs in unique. ways
• App builder: we believe long term that the best experiences will not be in a chat interface. We have plans to add additional tools that will enable you to create powerful applications and workflows.
• ??? Let us know what you'd like to see! Join our community via the links below, we'd love to hear from you.

Community

Discord Blog Bluesky Twitter