Autocache

Autocache

  Intelligent Anthropic API Cache Proxy with ROI Analytics

Autocache is a smart proxy server that automatically injects cache-control fields into Anthropic Claude API requests, reducing costs by up to 90% and latency by up to 85% while providing detailed ROI analytics via response headers.

Motivation

Modern AI agent platforms like n8n, Flowise, Make.com, and even popular frameworks like LangChain and LlamaIndex don't support Anthropic's prompt caching—despite users building increasingly complex agents with:

- 📝 Large system prompts (1,000-5,000+ tokens)
- 🛠️ 10+ tool definitions (5,000-15,000+ tokens)
- 🔄 Repeated agent interactions (same context, different queries)

The Problem

When you build a complex agent in n8n with a detailed system prompt and multiple tools, every API call sends the full context again—costing 10x more than necessary. For example:

- Without caching: 15,000 token agent → $0.045 per request
- With caching: Same agent → $0.0045 per request after first call (90% savings)

Real User Pain Points

The AI community has been requesting this feature:

- 🔗 n8n GitHub Issue #13231 - "Anthropic model not caching system prompt"
- 🔗 Flowise Issue #4289 - "Support for Anthropic Prompt Caching"
- 🔗 n8n Community Request - Multiple requests for caching support
- 🔗 LangChain Issue #26701 - Implementation difficulties

The Solution

Autocache works as a transparent proxy that automatically analyzes your requests and injects cache-control headers at optimal breakpoints—no code changes required. Just point your existing n8n/Flowise/Make.com workflows to Autocache instead of directly to Anthropic's API.

Result: Same agents, 90% lower costs, 85% lower latency—automatically.

Alternatives & Comparison

Several tools offer prompt caching support,…