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askimo

AI Client for chat, RAG, plans, MCP tools, and agents. Support multiple LLMs (Anthropic, OpenAI, VertexAI, vLLM, Nvidia NIM, Gemini, OpenRouter)

Links

Repository

README

From the repo.

Askimo - AI toolkit for your workflows.

One app. Every AI model. Your files stay local.

Chat · Search your files and the web · Run scripts · Build multi-step AI workflows · Execute AI agent skills - all offline-capable, all on your machine.

⭐ If Askimo saves you time, a star helps others find it - and keeps the project going. Star on GitHub →

Build License Release DCO

Total Downloads macOS Windows Linux

OpenAI Claude Gemini Grok Ollama LMStudio DockerAI OpenRouter NVIDIA NIM Together AI vLLM Server OpenAI-Compatible

📥 Download • 📖 Documentation • 💬 Discussions

askimo-ai/askimo | Trendshift

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:

Askimo Plans Demo

RAG - search and chat with your local files:

Askimo RAG Demo

MCP tools - connect any MCP-compatible server:

Askimo MCP Demo

Provider Switching MCP Tools Configuration RAG

Quick Start

Download for macOS, Windows, or Linux →

  1. Install and open Askimo
  2. Add a provider - paste an API key (OpenAI, Claude, Gemini…) or point it at a running Ollama instance
  3. Start chatting

Full setup guide →

System Requirements

OSmacOS 11+, Windows 10+, Linux (Ubuntu 20.04+, Debian 11+, Fedora 35+)
Memory50–300 MB (AI models require additional memory depending on provider)
Disk250 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

ModuleDescription
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.

Crowdin

Help translate Askimo →

License

AGPLv3. See LICENSE.

Contributing

Bug reports, feature requests, and pull requests are welcome. See CONTRIBUTING.md for details.

Contributors

Collected info

  • ★ 286 stars
  • ⎇ 57 forks
  • Language: Kotlin
  • Source updated: 8/4/2026

Config for your environment

Replace {MCP_ENDPOINT_URL} with this MCP’s endpoint URL (from its repo or docs above). No API key — you connect directly.

Tool

OS

Config file: ~/.cursor/mcp.json

{
  "mcpServers": {
    "mcp-server": {
      "url": "{MCP_ENDPOINT_URL}"
    }
  }
}

Paste into mcpServers in the config file. Restart Cursor after saving.

If this MCP is also published on mcpchannel.ai, you can subscribe from Browse and use the gateway config there instead.