How to Reduce LLM Token Costs by 85%
The Token Cost Problem
Every LLM API call costs money. GPT-4, Claude, and Gemini all charge per token — and context windows are getting larger, not cheaper. A typical coding agent session can burn through 100K+ tokens per task.
The math is simple: if you can compress your context by 85% without losing meaning, you save 85% on token costs.
What is Semantic Compression?
Semantic compression goes beyond simple text truncation. Instead of cutting text at an arbitrary character limit, it:
The result reads naturally and preserves the information an LLM needs to produce high-quality outputs.
Getting Started
1. Create an account
Sign up at gotcontext.ai — the free tier includes 1,000 compressions/month.
2. Generate an API key
Go to your dashboard settings and create a new API key.
3. Connect via MCP
Add to your Claude Code config:
``json
{
"mcpServers": {
"gotcontext": {
"url": "https://api.gotcontext.ai/mcp",
"headers": {
"Authorization": "Bearer gc_live_YOUR_API_KEY"
}
}
}
}
`
4. Start saving
Your AI tool will now automatically have access to compression tools. Add a note to your CLAUDE.md:
`
When context is large (>10K tokens), use gotcontext's ingest_context tool to compress before processing.
``
Real-World Results
| Document Type | Original | Compressed | Savings | | Large codebase (50 files) | 48,000 tokens | 7,200 tokens | 85% |
When to Compress
Compression works best for:
It's less useful for: