# DeepMem [Health: Active]
**Category:** 🧠 Knowledge & Memory
**Repository:** https://github.com/deepmemteam/deepmem
**GitHub Stars:** 113
**Views:** 0
**Installs:** 0
**Upvotes:** 0
**Directory Page:** https://allmcps.com/mcp/deepmem
## Description
Mem0-compatible persistent memory for AI agents: write facts once, recall them semantically.
## Claude Desktop Quick Installation
Install path detected from listing signals. Uses `uvx` (confidence: high):
```json
"mcpServers": {
"deepmem": {
"command": "uvx",
"args": ["deepmem-client"]
}
}
```
## Documentation & README
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:
```python
# 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
```
```bash
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](https://deepmem.dev)** - same API, no
> infra. Sign up, grab a key (`dm_live_...`), 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.
```bash
pip install deepmem-client
```
```python
# 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
- **`add(infer=True)` (the default) is asynchronous on DeepMem cloud** - it
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.
- **No graph relations** - DeepMem uses hybrid vector retrieval (vector + BM25
+ time-decay), so `relations` is always `[]`. Mem0's graph features aren't
replicated.
- **`reset` differs** - Mem0's is account-wide; DeepMem's is per-`user_id` with
a confirm guard.