OpenClaw + Ollama: Turn Your Local LLM into a Multi-Platform AI Assistant (2026)

Contains affiliate links. Disclosure.

OpenClaw is a multi-platform AI assistant — web UI, API, Telegram, Discord, Slack, and more — all fronting a single LLM backend. Connect it to Ollama and your local model becomes usable everywhere: from your phone via Telegram, from code via API, from the web dashboard. No data leaves your machine. This guide covers setup, config, use cases, and connecting multiple backends (Ollama + Anthropic + OpenAI) on a Liquid Web VPS.

What Is OpenClaw?

OpenClaw is an AI assistant framework that:

• Unifies backends — Ollama, OpenAI, Anthropic, or custom APIs
• Multi-platform — web, Telegram, Discord, Slack, WhatsApp, etc.
• Agent capabilities — browsing, RAG, tools (via ClawHub skills)
• Self-hosted — you run it on your server

When configured with Ollama, all LLM inference happens locally. OpenClaw handles routing, conversation state, and integrations.

What You Can Do with OpenClaw + Ollama

• Coding assistant — Connect Codestral or Llama 3 via Ollama for code completion and review
• Document Q&A — Use RAG mode with ChromaDB or other vector stores; Ollama answers from your docs
• Multi-turn research — Agent browses the web, summarizes, and uses Ollama for synthesis
• Multi-platform — Same assistant on Telegram, web, and API — one Ollama instance

Setup: OpenClaw Pointing to Ollama

Prerequisites

• Ollama running (locally or on another container)
• OpenClaw (Docker or binary)

Config for Ollama

Create or edit ~/.openclaw/config.yaml:

llm:
  provider: ollama
  base_url: http://host.docker.internal:11434   # When OpenClaw in Docker, Ollama on host
  # base_url: http://ollama:11434                 # When both in same Docker network
  model: llama3.2

agent:
  max_steps: 50
  timeout_seconds: 300
  browser:
    enabled: true
    headless: true

server:
  port: 18789
  host: 0.0.0.0

logging:
  level: info
  format: json

Docker Compose (Ollama + OpenClaw)

services:
  ollama:
    image: ollama/ollama:latest
    restart: unless-stopped
    ports:
      - "11434:11434"
    volumes:
      - ollama:/root/.ollama

  openclaw:
    image: ghcr.io/openclaw/openclaw:latest
    restart: unless-stopped
    ports:
      - "18789:18789"
    volumes:
      - ~/.openclaw:/root/.openclaw
    environment:
      - OLLAMA_BASE_URL=http://ollama:11434
    depends_on:
      - ollama

volumes:
  ollama:

For Ollama on the host and OpenClaw in Docker, use host.docker.internal:11434 and --add-host=host.docker.internal:host-gateway.

Configuration: Model Selection and Presets

• model — e.g. llama3.2, codestral, mistral, phi3:mini
• system prompt — Set in config or per-conversation in the dashboard
• ClawHub skills — Install web search, code execution, etc. for agent capabilities

Example with a coding preset:

llm:
  provider: ollama
  base_url: http://ollama:11434
  model: codestral

agent:
  system_prompt: "You are a helpful coding assistant. Prefer concise, actionable answers."

Use Cases

Coding assistant — Use Codestral or Llama 3.2 via Ollama. Ask via Telegram or web. Use ClawHub code skills for execution.

Document Q&A (RAG) — Index docs with a vector store (ChromaDB, Qdrant). OpenClaw retrieves context and sends to Ollama. See local RAG chatbot guide with Ollama and ChromaDB.

Multi-turn research — Enable browser skill. User asks "What's the latest on X?" — OpenClaw browses, gathers info, Ollama synthesizes the answer.

Connecting OpenClaw to Multiple Backends

OpenClaw can use several backends: Ollama for local, Anthropic or OpenAI for tasks that need stronger models.

# Example: primary Ollama, fallback Claude
llm:
  provider: anthropic
  api_key: "${ANTHROPIC_API_KEY}"
  model: claude-sonnet-4-5
  fallback:
    provider: ollama
    base_url: http://ollama:11434
    model: llama3.2

Or use different models per integration (e.g. Ollama for Telegram, Claude for web) if your setup supports it.

Privacy: All Processing Local with Ollama

When OpenClaw uses only Ollama:

• No API calls to OpenAI, Anthropic, or others
• Data stays on your server — conversations, documents, context
• No per-token cost — only hardware (electricity, VPS)

Ideal for sensitive use cases, air-gapped setups, or cost control. Use a Liquid Web VPS or GPU server for reliable 24/7 operation.

OpenClaw vs Continue.dev vs Open WebUI

Feature	OpenClaw	Continue.dev	Open WebUI
Primary interface	Multi-platform (Telegram, web, API)	IDE extension	Web chat
Local LLM	Yes (Ollama, etc.)	Yes	Yes (Ollama)
Agent / browsing	Yes (skills)	Limited	Plugins
Integrations	20+ platforms	VS Code, Cursor	Web, API
Best for	Unified assistant across devices	In-IDE coding	ChatGPT-style web UI

OpenClaw excels when you want one assistant everywhere — web, phone, API — all backed by Ollama.

ClawHub Skills and Extensions

OpenClaw supports ClawHub skills — plugins that add web search, code execution, file access, and more. Install via the dashboard or CLI: openclaw skills install @clawhub/web-search. With Ollama as the backend, the agent uses these skills to gather information and Ollama synthesizes the response. Combine with Apify for web scraping and data pipelines when the assistant needs live data.

Deployment Options

• Docker — Easiest. Use the Self-Host OpenClaw Complete Guide for full setup with Caddy, Telegram, and backups. For a simpler web UI, Ollama + Open WebUI offers a ChatGPT-like interface.
• Bare metal — Run OpenClaw and Ollama as systemd services on a Liquid Web VPS.
• GPU server — For faster inference, use a GPU VPS. Point OpenClaw at Ollama running on the same host with GPU access.

For full deployment (HTTPS, Telegram, backups), see Self-Host OpenClaw Complete Guide. For a simpler web-only chat, use Ollama + Open WebUI.

Start with Ollama only

Use Ollama as the sole backend first. Verify chat works across web and Telegram. Add Anthropic/OpenAI later if you need fallback or specific capabilities.

Frequently Asked Questions

OpenClaw is a multi-platform AI assistant that connects to LLM backends like Ollama, OpenAI, and Anthropic. It provides web UI, API, Telegram, Discord, Slack, and more from one deployment.

Yes. Set llm.provider to ollama, base_url to your Ollama endpoint (e.g. http://ollama:11434), and model name. All inference runs locally.

Create a bot via @BotFather, get the token. In OpenClaw dashboard → Integrations → Telegram, paste the token. Message the bot to start chatting. It uses your configured Ollama backend.

Yes. Configure multiple providers. Use fallback so Ollama handles most requests and Claude/OpenAI for complex tasks. Or route different integrations to different backends if supported.

On your server. OpenClaw stores conversation state in ~/.openclaw. Ollama runs models locally. No data is sent to third-party APIs unless you add OpenAI/Anthropic.