Why Askimo?
You shouldn't have to choose between the best AI model, your privacy, and getting real work done.
- One app, every model. Stop juggling browser tabs. Chat with OpenAI, Claude, Gemini, Grok, or a local Ollama model, switch in seconds, no copy-pasting.
- Built as a native desktop app. Not a web wrapper. Starts fast, runs lean, and stays responsive even after hours of use and thousands of messages in a single conversation.
- Long conversations that actually work. No crashes, no tab reloads, no lost context. Askimo handles deep, extended sessions the way a real desktop app should.
- Your files stay on your machine. Search and chat with your own documents using local RAG. Nothing is uploaded. Nothing leaves your device.
- More than just chat. Run Python/Bash scripts, chain multi-step AI workflows, and connect MCP tools, all from the same app.
See It in Action
Multi-step AI Plans - fill in a form, get a finished deliverable:
RAG - search and chat with your local files:
MCP tools - connect any MCP-compatible server:
Quick Start
Download for macOS, Windows, or Linux →
- Install and open Askimo
- Add a provider - paste an API key (OpenAI, Claude, Gemini…) or point it at a running Ollama instance
- Start chatting
System Requirements
| OS | macOS 11+, Windows 10+, Linux (Ubuntu 20.04+, Debian 11+, Fedora 35+) |
| Memory | 50–300 MB (AI models require additional memory depending on provider) |
| Disk | 250 MB |
Features
- Multi-provider - Switch between OpenAI, Claude, Gemini, Grok, Ollama, LM Studio, Docker AI, OpenRouter, NVIDIA NIM, Together AI, vLLM Server, or any OpenAI-compatible endpoint per session
- Web search (multiple backends) - Search the web with DuckDuckGo (no API key), Brave Search API, Tavily, or your own SearxNG instance
- Local RAG - Index local folders, files, and web URLs. Hybrid BM25 + vector retrieval with an AI classifier that skips retrieval when the query doesn't need it. Your data never leaves your machine.
- Plans (agentic workflows) - Chain multi-step AI pipelines from a form UI. Each step builds on the previous; progress shown live. Export as PDF or Word. Define your own plans in YAML or generate them by describing your workflow in plain English.
- Script runner - Execute Python, Bash, and JavaScript from chat. Python runs in an auto-managed virtualenv with automatic dependency installation.
- MCP tool integration - Connect MCP-compatible servers via stdio or HTTP
- Persistent sessions - Conversations stored in a local SQLite database, restored on restart
- Vision - Attach images to conversations; works with any multimodal model
- Local telemetry - Token usage, cost estimates, RAG performance per provider. Nothing uploaded.
- i18n - English, Chinese (Simplified & Traditional), Japanese, Korean, French, Spanish, German, Portuguese, Vietnamese
Supported Providers
Cloud: OpenAI · Anthropic Claude · Google Gemini · xAI Grok · OpenRouter · NVIDIA NIM · Together AI
Local: Ollama · LM Studio · Docker AI · vLLM Server
Custom: Any OpenAI-compatible endpoint via custom base URL
Building from Source
Prerequisites
- JDK 25+
- Git
git clone https://github.com/askimo-ai/askimo.git
cd askimo
Run the desktop app
./gradlew :desktop:run
Build native installers
./gradlew :desktop:package
Project Structure
| Module | Description |
|---|---|
desktop/ |
Compose Multiplatform desktop application |
desktop-shared/ |
Shared UI components |
shared/ |
Core: providers, RAG, MCP, memory, tools, database, plans engine, skills & agent runtimes |
See CONTRIBUTING.md for development guidelines and DCO requirements, or the Development Getting Started Guide.
Localization
English · 中文 (简体/繁體) · 日本語 · 한국어 · Français · Español · Deutsch · Português · Tiếng Việt
Translations are managed on Crowdin. Contributions welcome - no coding required.
License
AGPLv3. See LICENSE.
Contributing
Bug reports, feature requests, and pull requests are welcome. See CONTRIBUTING.md for details.