Surreal Memory

Surreal-Memory

[](https://pypi.org/project/surreal-memory/) [](https://github.com/acidkill/surreal-memory/actions) [](https://www.python.org/downloads/) [](https://opensource.org/licenses/MIT) [](https://surrealdb.com/)

**Persistent graph memory for AI agents, powered by SurrealDB.**

All features are free and open source. No license keys. No paywalls. No embedding API required for basic usage.

pip install surreal-memory[surrealdb]
smem init --full

Restart your AI tool. Your agent now remembers.

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Why Surreal-Memory?

Most AI memory tools are vector databases with a search API bolted on. Surreal-Memory is a **graph that thinks** — memories are stored as interconnected neurons and recalled through spreading activation, backed by SurrealDB's multi-model engine (document + graph + vector in one database).

Query: "Why did Tuesday's outage happen?"

Surreal-Memory traces the chain:
outage ← CAUSED_BY ← JWT expiry ← SUGGESTED_BY ← Alice's review

**Relationships are explicit** — `CAUSED_BY`, `LEADS_TO`, `RESOLVED_BY`, `CONTRADICTS` — so your agent doesn't just find memories, it *reasons* through them.

	RAG / Vector Search	Surreal-Memory
Backend	Pinecone / Chroma	SurrealDB (doc + graph + vector)
Retrieval	Similarity score	Graph traversal + vector search
Relationships	None	41 explicit synapse types
LLM required	Yes (embeddings)	No — works fully offline
Multi-hop reasoning	Multiple queries	One traversal
Memory lifecycle	Static	Decay, reinforcement, consolidation
Cost per 1K queries	~$0.02	$0.00

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