Stop rebuilding RAG pipelines. Extremis gives any AI agent layered, learning memory in two lines of config — local SQLite, Postgres, Chroma, or Pinecone.
pip3.11 install extremis
one click · auto-provisions Postgres · memory lives in the cloud
Every conversation logs durably. Every recalled memory gets scored. Every night the logs distil into structured knowledge.
Append to a fsync'd JSONL log and write to the episodic store in one call. Durable before any embedding happens.
Semantic search ranked by cosine × RL score × recency. Identity and procedural memories always included. Every result ships with a plain-English reason.
Mark recalled memories useful (+1) or harmful (-1). Negative signals apply 1.5× weight — same asymmetry human threat-memory uses.
The "dream pass" — reads new log entries, calls Claude Haiku to extract durable semantic and procedural facts, advances the checkpoint. Safe to re-run.
No API key needed. No account required.
pip install extremis says "no matching distribution found", your default
python3 is older. Check: python3 --version
brew install python@3.11 then use
pip3.11 install extremis
sudo apt install python3.11 python3.11-pip
·
Windows: python.org/downloads
# First: confirm you have Python 3.11+ python3.11 --version # Core — local SQLite, sentence-transformers (no API key) pip3.11 install extremis # + MCP server for Claude Desktop / Code pip3.11 install "extremis[mcp]" # + Postgres, Chroma, Pinecone, OpenAI embeddings, hosted server pip3.11 install "extremis[all]"
from extremis import Extremis, MemoryLayer mem = Extremis() # stores in ~/.extremis/ by default # Store mem.remember("User is building a WhatsApp AI", conversation_id="c1") mem.remember_now("Always ask about deadlines first", layer=MemoryLayer.PROCEDURAL) # Recall — every result explains why it ranked here results = mem.recall("what is the user building?") for r in results: print(r.memory.content) print(r.reason) # "similarity 0.87 · score +2.0 · used 5× · 3d old" # Reinforcement — good memories surface first over time mem.report_outcome([r.memory.id for r in results[:2]], success=True) # Try the demo # $ extremis-demo
Most memory systems are cosine search over a flat vector DB. Extremis is different in five ways.
Recency decay + 1.5× asymmetric RL weighting. Unimportant things fade. Mistakes stick harder. The same pattern human threat-memory uses.
r.reason — "similarity 0.91 · score +4.0 · used 8× · 3d old". Every result tells you exactly why it ranked there. Auditable. Debuggable. No black box.
Multiple agents share one namespace. Research agent stores, writing agent recalls. Agent teams ship as one brain.
SQLite locally. Postgres in staging. Pinecone in production. One env var. Migrate between any two with extremis-migrate.
Entities, relationships, attributes. Answers "who does Alice work for" — the structural question vectors can't.
Plug into Claude Desktop or Claude Code with two lines of config. Nine tools, no code required.
| Feature | Extremis | Mem0 | LangChain | Raw Pinecone |
|---|---|---|---|---|
| RL-scored retrieval | ✓ | ✗ | ✗ | ✗ |
| Memory explains itself | ✓ | ✗ | ✗ | ✗ |
| Knowledge graph | ✓ | ✗ | ✗ | ✗ |
| Backend-agnostic | ✓ 4 backends | Cloud only | Manual | — |
| MCP server | ✓ 9 tools | ✗ | ✗ | ✗ |
| Self-hostable | ✓ | ✗ | ✓ | ✓ |
| Migration CLI | ✓ | ✗ | ✗ | — |
| Open source (MIT) | ✓ | Partial | ✓ | ✗ |
Local by default. Cloud when you need it. Nothing stored anywhere you didn't choose.
Everything in ~/.extremis/ on your machine. Zero setup, zero cost, works offline.
# zero config needed from extremis import Extremis mem = Extremis()
Point at any cloud Postgres. Supabase and Neon both have free tiers with pgvector built in. Works from any machine.
pip3.11 install "extremis[postgres]" EXTREMIS_STORE=postgres EXTREMIS_POSTGRES_URL=postgresql://...
Fully managed serverless vector store. Vectors live in Pinecone cloud. Free starter tier available.
pip3.11 install "extremis[pinecone]" EXTREMIS_STORE=pinecone EXTREMIS_PINECONE_API_KEY=pk_...
Deploy the server to Railway. Memory lives in Railway's Postgres — persistent across restarts. Client has zero local footprint.
⚠️ Don't use SQLite on Railway — container filesystems are ephemeral. Always pair with Railway Postgres.
Render auto-provisions Postgres alongside the server via render.yaml.
Memory lives in Render's managed Postgres — persistent across restarts.
Getting your API key:
On first startup, extremis prints a key in the server logs.
Go to your service → Logs tab → look for
extremis — FIRST START.
The key starts with extremis_sk_....
from extremis import HostedClient mem = HostedClient( api_key="extremis_sk_...", # from logs base_url="https://your-app.onrender.com" )
remember(), recall(), report_outcome().
Switch backends with one env var. Migrate between any two with extremis-migrate.
Claude Desktop and Claude Code supported out of the box.
# Requires Python 3.11+ (check: python3.11 --version) # 1. Install pip3.11 install "extremis[mcp]" # 2. Add to Claude Desktop config # ~/Library/Application Support/Claude/ # claude_desktop_config.json { "mcpServers": { "extremis": { "command": "/opt/homebrew/bin/extremis-mcp" } } } # 3. Restart Claude Desktop
No cloud. No tracking. No data leaving your machine unless you explicitly choose it.
All memories, logs, and knowledge graph data are written to
~/.extremis/
on your own machine. No account required. No sign-up. Nothing sent anywhere.
The conversation log is a JSONL file on your disk. The memory store is a SQLite database. Both are readable with any text editor. You can inspect, export, or delete them at any time.
The optional memory_consolidate tool
sends recent conversation log entries to Claude Haiku (via your own Anthropic API key) to extract
structured memories. You control this — it only runs when you explicitly call it,
and only uses your key, billed to you directly.
Switch to Postgres, Chroma, or Pinecone when you need scale — or keep SQLite forever. If you use an external backend, your data goes there under your own credentials. Extremis itself never sees it.
Extremis collects no usage data, sends no analytics, and has no home-call behaviour. It's a library that runs entirely in your process. You can verify this — it's open source.
Need a REST API for a team? Run extremis-server
on your own infrastructure. The hosted server code is open source and ships with a
Docker Compose file. We offer a managed cloud option for convenience, not necessity.