DeepMem MCP server

DeepMem Drop-in AI memory layer with 2× faster response and 10× lower cost. Fully compatible with Mem0 API. Migrate in 5 minutes - one import line. Self-hostable. No auth, no payment, no lock-in. Or use the managed cloud at deepmem.dev.

Cloud · Self-host · Benchmarks · Reproduce them

Migrate from Mem0 in one line - same MemoryClient, same method signatures:

# Before - Mem0
from mem0 import MemoryClient
client = MemoryClient(api_key="m0-...")

# After - DeepMem (only the import changes)
from deepmem import MemoryClient
client = MemoryClient(api_key="dm_live-...")   # get a key at deepmem.dev

pip install deepmem-client

Turn conversations into searchable long-term memory: a FastAPI HTTP API in front of a Qdrant vector store, with LLM fact extraction, hybrid retrieval (vector + BM25 + entity boost + time-decay), semantic caching, async batched distillation, GDPR controls, and a built-in MCP server. It runs in open mode - no API key, no user registration - so you can deploy it for your own agents in minutes. Multi-tenant isolation is driven by user_id in the request body.

Prefer not to self-host? DeepMem Cloud is the managed version of

this exact engine at deepmem.dev - same API, no

infra. Sign up, grab a key (dmlive...), point your base URL at

https://deepmem.dev, done. The cloud and the open-source server speak the

same Mem0-compatible API, so client code is identical.

Migrate from Mem0

Already using Mem0? Switch to DeepMem cloud in one line. The deepmem-client package mirrors mem0.MemoryClient - same class name, same method signatures, same filters={"user_id": ...} style - so everything after the import stays untouched.

pip install deepmem-client

# before (Mem0)
from mem0 import MemoryClient
client = MemoryClient(api_key="m0-...")
client.add(messages, user_id="alex")
client.search("What can Alex cook?", filters={"user_id": "alex"})

# after (DeepMem cloud) - change one import line
from deepmem import MemoryClient
client = MemoryClient(api_key="dm_live_...")        # key at https://deepmem.dev
client.add(messages, user_id="alex")                # identical calls
client.search("What can Alex cook?", filters={"user_id": "alex"})

Behavioral notes

returns pending=True with results=[] and extracted facts land a few seconds later. (Mem0 cloud's add is async too - it returns PENDING.) Pass infer=False for synchronous raw-text storage that's immediately searchable.

• add(infer=True) (the default) is asynchronous on DeepMem cloud - it

replicated.

• No graph relations - DeepMem uses hybrid vector retrieval (vector + BM25
• time-decay), so relations is always []. Mem0's graph features aren't

a confirm guard.

• reset differs - Mem0's is account-wide; DeepMem's is per-user_id with

Pricing

DeepMem Cloud is 10x cheaper than Mem0 at every paid tier - the same shape of plans, a tenth of the price.

Shortened. The full README is on GitHub.