cachly 0.1.0

Official Python SDK for cachly.dev – Managed Valkey/Redis cache with semantic AI caching

Stop Rebuilding Context. Start Shipping Faster.

cachly Python SDK — The cache that remembers everything so your AI assistant doesn't have to start from scratch every morning.

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The Problem Nobody Talks About

You open Cursor. You ask it to continue where you left off. It doesn't know what "where you left off" means.

You explain your architecture. Again.
You explain why you use that pattern. Again.
You explain the bug you fixed last Tuesday. Again.

The average developer wastes 45 minutes per day just re-establishing context with their AI assistant. That's 3.5 hours a week. 180 hours a year. Gone.

And then there's the infrastructure tax: your AI hits your database for every request. Your LLM bills are exploding. Your p99 is embarrassing. Your GDPR officer won't stop emailing you about US data residency.

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cachly fixes both.

Two products. One connection string. Zero ops.

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🧠 AI Dev Brain — Your AI Assistant's Permanent Memory

Give Claude Code, Cursor, GitHub Copilot, and Windsurf a brain that persists across every session, every machine, every restart:

npx @cachly-dev/init

From this moment, your AI assistant will:

• Remember every bug fix and the exact command that solved it
• Know your architecture without you explaining it again
• Resume work exactly where you left off, every single session
• Reuse known solutions instead of re-researching — saving ~1,200 tokens per recall

Before cachly: "Let me analyze your codebase... reading 47 files..."
After cachly: "Last session: deployed blue/green API, 23 lessons stored. Ready."

Configure in ~/.vscode/mcp.json, .cursor/mcp.json, or .mcp.json:

{
  "servers": {
    "cachly": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@cachly-dev/mcp-server"],
      "env": { "CACHLY_JWT": "your-jwt-token" }
    }
  }
}

→ Full docs: cachly.dev/docs/ai-memory

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⚡ Managed Cache — Sub-millisecond, GDPR-Compliant, German Servers

Installation

pip install cachly
# or
uv add cachly

Quick Start

import os
from cachly import CachlyClient

cache = CachlyClient(url=os.environ["CACHLY_URL"])

# Cache LLM responses, user sessions, computed results
cache.set("user:42", {"name": "Alice"}, ttl=300)
user = cache.get("user:42")

# Get-or-Set: never hit the DB twice
report = cache.get_or_set("report:monthly", lambda: db.run_expensive_report(), ttl=3600)

# Atomic counter
views = cache.incr("page:views")

cache.close()

Create your free instance → No credit card. Live in 30 seconds.

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With vs. Without cachly

Situation	Without cachly	With cachly
AI session start	5–10 min re-explaining context	< 10 sec, full context loaded
Same DB query, 1000 req/s	1,000 DB hits	1 DB hit, 999 cache hits
LLM API costs for repeated prompts	Pay every time	Pay once, cache the rest
GDPR compliance for EU users	Data leaves EU (US Redis)	Data stays in Germany, always
Infra setup	Days of ops work	30 seconds, zero ops
Architecture knowledge after holiday	Starts from zero	Fully briefed in seconds
Debugging a known issue	Re-research from scratch	Instant: "you fixed this on March 12"
p99 latency (uncached)	200–800ms (DB)	< 1ms (cache hit)

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Semantic Cache — Cut LLM Costs by 40–70%

Stop paying for the same answer twice:

sem = cache.semantic_cache(embed_fn=openai.embed, threshold=0.92, ttl=86400)

result = sem.get(user_query)
if result is None:
    answer = call_your_llm(user_query)
    sem.set(user_query, answer)

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👥 Team Brain — Shared AI Memory for Your Whole Team

One shared instance. Every developer gets smarter every day.

# .env — same instance for the whole team
CACHLY_INSTANCE_ID=your-shared-team-instance

# Alice fixes a bug, stores the lesson:
brain.learn_from_attempts(
    topic="deploy:k8s-timeout",
    outcome="success",
    what_worked="Increase readinessProbe.failureThreshold to 10",
    author="alice"
)

# Bob starts a session the next day:
brain.session_start()
# → "💡 alice solved deploy:k8s-timeout 1d ago: Increase readinessProbe..."

Set up a team org at cachly.dev/teams — Team €99/mo · 10 seats · Business €299/mo · 50 seats.

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Pricing

Tier	RAM	Price	Best for
Free	25 MB	€0/mo	Dev & side projects
Dev	200 MB	€19/mo	Startups, small apps
Pro	900 MB	€49/mo	Production workloads
Speed	900 MB Dragonfly + Semantic Cache	€79/mo	AI apps, high QPS
Business	7 GB	€199/mo	Scale-ups

All plans: German servers · GDPR-compliant · No US data transfer · 99.9% SLA

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Links

• cachly.dev — Dashboard & free signup
• PyPI — Package
• AI Brain docs — MCP server setup
• GitHub