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The best MCP clients in 2026 compared: Askimo Desktop, Claude Desktop, Open WebUI, LibreChat, AnythingLLM, and Msty. MCP (Model Context Protocol) lets AI use real tools - GitHub, databases, local files, web search. This guide covers which chat client fits your workflow, what MCP features each supports, and how to get started in minutes.
MCP and function calling both let an AI use tools. But function calling is a per-request contract you define in code, while MCP is a persistent protocol that exposes tools from a running server. This guide explains the difference clearly, when each approach makes sense, and how tools like Askimo Desktop let you use both without writing any code.
Askimo App provides an Ollama GUI for running local AI models like Llama 3.3, DeepSeek R1, Mistral, Gemma 3, Qwen 2.5, and Phi-4. Features persistent history, in-chat search, starred conversations, and export options. Project-aware RAG enables chatting with your codebase or documents using local models with complete privacy. Switch seamlessly between Ollama and cloud providers. Includes lazy loading, custom directives, and automatic endpoint detection.
MCP (Model Context Protocol) lets your AI do real things, not just answer questions. Connect Askimo Desktop to GitHub, databases, local files, web search, and any API via Stdio or HTTP. Secrets stay in your OS keychain. Works with Claude, GPT, Gemini, and local Ollama models.
Askimo's RAG (Retrieval-Augmented Generation) with Ollama enables chatting with your documents, research papers, notes, and project files using local AI models like Llama, Mistral, and Phi. Automatically index PDFs, Word documents, spreadsheets, and text files with smart search. Ask questions about your content in plain English - all locally with zero data leaving your machine. Perfect for researchers, writers, students, and anyone managing large collections of documents.
New in Askimo: built-in terminal emulator, Model Context Protocol (MCP) integration, a RAG sources tree to inspect exactly what the assistant used, image-model support for multimodal workflows, and major desktop improvements across performance, reliability, and UX.
A comprehensive technical deep dive into building Askimo - an open-source desktop AI chat client for ChatGPT, Claude, Gemini, and Ollama built with Kotlin and Compose. Learn how we architected support for multiple AI models, handled concurrent streaming, implemented RAG for documents, and solved real-world challenges in production.
The best AI desktop app isn't the one with the best single model - it's the one that lets you use ChatGPT, Claude, Gemini, and Ollama together. Switch models mid-conversation, keep sensitive data local, and cut API costs by routing simple tasks to free local models. Askimo is free, open source, and works on macOS, Windows, and Linux.
Compare top 5 Ollama desktop clients for 2026. Askimo excels with native performance, multiple AI models support, and RAG-powered project indexing. LM Studio offers easy model management. Open WebUI provides self-hosted team workflows. AnythingLLM focuses on document RAG for chatting with PDFs. Chatbox delivers minimal, lightweight chat. All support local-first privacy but differ in performance, RAG capabilities, and features. Includes setup guides and use-case recommendations.
Major Askimo App update adds multilingual support for 10+ languages including English, Vietnamese, Chinese, Japanese, Korean, French, German, Spanish, Portuguese, and Italian. Introduces 18 themes with light, dark, and system-adaptive options. New developer tools include real-time resource monitoring, enhanced debugging, and granular log controls. Significant performance improvements especially on Windows, plus better error handling across all platforms.
Askimo App complements the CLI for interactive AI work. Switch between OpenAI, Claude, Gemini, and Ollama in one session without separate browser tabs. The app maintains your workspace and conversation context when switching providers. Start with OpenAI, jump to Gemini, or use local Ollama models seamlessly. Features offline support, secure storage, and native cross-platform performance for unified AI workflows.
