Run OpenClaw/Clawdbot for FREE with Lynkr (No API Bills)

Your personal AI assistant running 24/7 — without burning through API credits

If you’ve tried OpenClaw (also known as Clawdbot), you know it’s incredible. An AI assistant that lives in WhatsApp/Telegram, manages your calendar, clears your inbox, checks you in for flights — all while you chat naturally.

But there’s a catch: it needs an LLM backend, and Anthropic API bills add up fast.

What if I told you that you can run OpenClaw completely free using local models? Enter Lynkr.

🔗 What is Lynkr?

Lynkr is a universal LLM proxy that lets you route OpenClaw requests to any model provider — including free local models via Ollama.

The magic? OpenClaw thinks it’s talking to Anthropic, but Lynkr transparently routes requests to your local GPU instead.

💡 Why This Matters

Problem with direct Anthropic API:

💸 Bills explode quickly (OpenClaw runs 24/7)
⚠️ Potential ToS concerns with automated assistants
🔒 Your data goes to external servers

With Lynkr + Ollama:

✅ $0/month — runs entirely on your machine
✅ ToS compliant — no API abuse concerns
✅ 100% private — data never leaves your computer
✅ Smart fallback — route to cloud only when needed

🚀 Setup Guide (15 minutes)

Step 1: Install Ollama

# macOS/Linux
curl -fsSL https://ollama.com/install.sh | sh

# Pull Kimi K2.5 (recommended for coding/assistant tasks)
ollama pull kimi-k2.5

# Also grab an embeddings model for semantic search
ollama pull nomic-embed-text

Step 2: Install Lynkr

# Option A: NPM (recommended)
npm install -g lynkr

# Option B: Clone repo
git clone https://github.com/Fast-Editor/Lynkr.git
cd Lynkr
npm install

Step 3: Configure Lynkr

Create your .env file:

# Copy example config
cp .env.example .env

Edit .env with these settings:

# Primary provider: Ollama (FREE, local)
MODEL_PROVIDER=ollama
OLLAMA_MODEL=kimi-k2.5
OLLAMA_ENDPOINT=http://localhost:11434

# Enable hybrid routing (local first, cloud fallback)
PREFER_OLLAMA=true
OLLAMA_MAX_TOOLS_FOR_ROUTING=3

# Fallback provider (optional - for complex requests)
FALLBACK_ENABLED=true
FALLBACK_PROVIDER=openrouter
OPENROUTER_API_KEY=sk-or-v1-your-key  # Only needed if using fallback

# Embeddings for semantic search
OLLAMA_EMBEDDINGS_MODEL=nomic-embed-text

# Token optimization (60-80% cost reduction on cloud fallback)
TOKEN_TRACKING_ENABLED=true
TOOL_TRUNCATION_ENABLED=true
HISTORY_COMPRESSION_ENABLED=true

Step 4: Start Lynkr

# If installed via npm
lynkr

# If cloned repo
npm start

You should see:

🚀 Lynkr proxy running on http://localhost:8081
📊 Provider: ollama (kimi-k2.5)

Step 5: Configure OpenClaw/Clawdbot

In your OpenClaw configuration, set:

Setting	Value
Model/auth provider	`Copilot`
Copilot auth method	`Copilot Proxy (local)`
Copilot Proxy base URL	`http://localhost:8081/v1`
Model ID	`kimi-k2.5`

That’s it! Your OpenClaw now runs through Lynkr → Ollama → Kimi K2.5, completely free.

⚡ How Hierarchical Routing Works

The killer feature is smart routing:

OpenClaw Request
       ↓
   Is it simple?
    /        
  Yes         No
   ↓           ↓
Ollama     Cloud Fallback
(FREE)     (with caching)

Lynkr analyzes each request:

Simple requests (< 3 tools) → Ollama (free)
Complex requests → Cloud fallback (with heavy caching/compression)

This means even if you enable cloud fallback, you’ll use it sparingly.

💰 Cost Comparison

Setup	Monthly Cost	Privacy
Direct Anthropic API	$100-300+	❌ Cloud
Lynkr + Ollama only	$0	✅ 100% Local
Lynkr + Hybrid routing	~$5-15	✅ Mostly Local

🔒 Why This is ToS-Safe

Running OpenClaw directly against Anthropic’s API at scale can raise ToS concerns (automated usage, high volume, etc.).

With Lynkr:

Local models = no external API terms apply
Your hardware = your rules
Fallback is minimal = within normal usage patterns

🧠 Advanced: Memory & Compression

Lynkr includes enterprise features that further reduce costs:

Long-Term Memory (Titans-inspired):

MEMORY_ENABLED=true
MEMORY_RETRIEVAL_LIMIT=5
MEMORY_SURPRISE_THRESHOLD=0.3

Headroom Compression (47-92% token reduction):

HEADROOM_ENABLED=true
HEADROOM_SMART_CRUSHER=true
HEADROOM_CACHE_ALIGNER=true

These features mean even when you hit cloud fallback, you’re using far fewer tokens.

🎯 Recommended Models

Use Case	Ollama Model	Pull Command
General Assistant	kimi-k2.5	`ollama pull kimi-k2.5`
Coding Tasks	qwen2.5-coder:latest	`ollama pull qwen2.5-coder:latest`
Fast/Light	llama3.2:3b	`ollama pull llama3.2:3b`
Embeddings	nomic-embed-text	`ollama pull nomic-embed-text`

🏃 TL;DR

# Install
curl -fsSL https://ollama.com/install.sh | sh
ollama pull kimi-k2.5
npm install -g lynkr

# Configure (.env)
MODEL_PROVIDER=ollama
OLLAMA_MODEL=kimi-k2.5
PREFER_OLLAMA=true

# Run
lynkr

# Point OpenClaw to http://localhost:8081/v1

Result: OpenClaw running 24/7, $0/month, 100% private.