Lynkr
An LLM Gateway which optimises your token usage.
87.6% fewer tokens on JSON tool results. 53% fewer tokens on tool-heavy requests. 171ms semantic cache hits. Zero code changes.
| 87.6% JSON Compression |
53% Tool Token Reduction |
171ms Semantic Cache Hits |
13+ LLM Providers |
0 Code Changes Required |
Numbers from a live benchmark against LiteLLM on identical workloads. See full report →
🚀 New: Wrap Mode for AI Coding Tools
Use Lynkr's routing with your AI coding assistant — maximize your subscription value:
npm install -g lynkr
# Claude Code Pro/Max
lynkr wrap claude
Wrapping gives you:
- ✅ Tier routing (send simple tasks to free Ollama, complex to your subscription/API)
- ✅ TOON/RTK compression (87% token reduction on tool outputs)
- ✅ Semantic caching (171ms cache hits)
- ✅ 3-5x more usage from the same subscription limits
- ✅ Works with OAuth (Claude, Copilot, Cursor) or API keys (Aider, Codex)
Quick Start (2 Minutes)
1. Install Lynkr
npm install -g lynkr
2. Configure Lynkr
The fastest path is the interactive wizard:
lynkr init
It asks four questions — usage mode (Claude Pro/Max via wrap, or direct API keys), tier picks for SIMPLE/MEDIUM/COMPLEX/REASONING across the 12 supported providers, credentials for what you chose, and a few routing-intelligence knobs — then writes a fully-populated .env with sensible production defaults for everything else (caching, compression, policy budgets, MCP sandbox, agents, rate limiting).
Useful flags:
lynkr init --force # overwrite an existing .env
See docs/init.md for the full wizard reference.
If you'd rather configure by hand, the manual options below still work — copy .env.example to .env and edit it directly:
Option A: Free & Local (Ollama) - Recommended for Testing
# Install Ollama first: https://ollama.com
ollama pull qwen2.5-coder:latest
Then start Lynkr:
lynkr start
3. Connect Your Tool
Cursor IDE
- Settings → Models → Override Base URL
- Set to:
http://localhost:8081/v1 - API Key:
any-value
Codex CLI
Edit ~/.codex/config.toml:
model_provider = "lynkr"
[model_providers.lynkr]
base_url = "http://localhost:8081/v1"
wire_api = "responses"
✅ Done! Your AI tool now uses your chosen provider.
Common Startup Errors
Error: unable to determine transport target for "pino-pretty"
Problem: You're running an older version (< 9.3.0).
Solution: Update to the latest version:
npm install -g lynkr@latest
If you must use an older version, set NODE_ENV=production before starting.
Warning: Missing tier configuration: TIER_SIMPLE, TIER_MEDIUM...
This is just a warning - you can ignore it. Tier routing is optional.
To remove the warning, add to .env:
TIER_SIMPLE=ollama:qwen2.5-coder:latest
TIER_MEDIUM=ollama:qwen2.5-coder:latest
TIER_COMPLEX=ollama:qwen2.5-coder:latest
TIER_REASONING=ollama:qwen2.5-coder:latest
Warning: FALLBACK_PROVIDER='databricks' is enabled but missing credentials
Solution: Add to .env:
FALLBACK_EN