Local AI Agent Stack 2026

The core of the stack. Install OpenClaw once and get 100+ prebuilt integrations — browser control, file management, email, calendar, messaging apps — without writing agent logic from scratch. It's model-agnostic: point it at Ollama for a fully local setup, or swap in Claude or GPT when you need heavier reasoning. MIT-licensed, 347K GitHub stars, active community. See our OpenClaw ecosystem guide →

One command installs a capable language model locally: ollama pull llama3.2. No API key, no usage bill, no data leaving your network. Runs Llama 3.2, DeepSeek-R1, Mistral, Phi-3, Qwen 2.5, and 50+ others. OpenClaw connects to Ollama out of the box — agents call local models through the same interface as cloud APIs.

The chat UI that sits on top of Ollama. Drop in your PDFs, notes, and Obsidian exports. AnythingLLM builds a local vector database and lets your agent answer 'what did my meeting notes say about the Q3 budget' without sending anything to a server. Connects to Ollama by default; one settings change switches it to Claude or GPT API.

Your agent's long-term memory. Keep notes, research logs, meeting summaries, and project context in Obsidian's plain-Markdown files — AnythingLLM ingests the vault directly. No sync to any cloud service unless you opt in. Obsidian is free for personal use; the paid Sync feature ($10/mo) is entirely optional.

Some tasks — long multi-step reasoning, complex code review, large document synthesis — push past what a local 7B model handles well. DeepSeek V3 costs roughly $0.07 per million input tokens: two to three orders of magnitude cheaper than GPT-4o or Claude Sonnet. Most builders spend under $2/month with light use. OpenClaw switches between Ollama and DeepSeek via a config flag.