Memory API

Persistent memory for AI agents. Not vector search — statistical learning.

Sign up free at console.mnemoverse.com — no credit card, 1K queries/day.

3 Lines of Python

from mnemoverse import MnemoClient

client = MnemoClient(api_key="mk_...")

# Store a memory
client.write("Retry with exponential backoff fixed the timeout issue",
             concepts=["retry", "backoff", "timeout"])

# Query — Hebbian associations expand "timeout" → "backoff", "retry"
results = client.read("how to handle timeouts?")

# Report outcome — system learns what works
client.feedback(atom_ids=[r.atom_id for r in results.items], outcome=1.0)

Not a Vector Database

	Mnemoverse	Pinecone / Weaviate / Chroma
Core model	Statistical learning (Rescorla-Wagner + Hebbian)	Vector embeddings (cosine similarity)
Learns from outcomes	Yes — feedback loop updates valence	No — static retrieval
Concept associations	Three-factor Hebbian graph	None
Memory compression	HDBSCAN consolidation + Von Restorff	Accumulate forever
Query expansion	Automatic via learned associations	Manual or none
Starting price	Free (1K queries/day)	$25-70/mo

We don't just store and retrieve. We learn which memories matter.

How It Works

1. WRITE  →  Importance gate filters noise  →  Stored with semantic embedding
2. READ   →  Hebbian expansion  →  Valence-boosted ranking  →  Results
3. FEEDBACK  →  Outcome updates valence  →  Strengthens associations
4. CONSOLIDATE  →  HDBSCAN clusters similar  →  Prototypes + singletons

Memories that lead to good outcomes rank higher in future queries. Memories that consistently fail get suppressed. The system improves with use.

Pricing

	Free	Pro	Team
Price	$0/mo	$29/mo	$149/mo
Queries/day	1,000	50,000	500,000
Atoms (memories)	10,000	500,000	5,000,000
Rate limit	60/min	600/min	3,000/min
API keys	1	Unlimited	Unlimited
Support	Community	Email	Slack

Built on Research

• Published: SLoD framework on arXiv (Semantic Level of Detail)
• Benchmarked: evaluated on LoCoMo (1,986 questions) and LongMemEval — see Benchmarks for the current numbers
• Validated: experiments across game-playing agents and academic benchmarks

Next Steps

• Getting Started — First API call in 2 minutes
• API Reference — Full endpoint documentation
• Python SDK — pip install mnemoverse
• MCP Server — Persistent memory for Claude and Cursor
• Security — Tenant isolation, data privacy, compliance