Saket Aryan
0d37619f24
The plugin README promises "anonymous usage events" and the telemetry module's docstring says it sends only "salted hashes". Neither is true. resolve_distinct_id() exchanges the API key for the account email and sends that as the distinct_id on every event. Installing the plugin requires an API key, so this is nearly every user. That is probably the behaviour we want — the Python SDK and the CLI attribute the same way — but the description has to match it. repo_hash and session_hash were unsalted SHA-256 cut to 16 hex characters. repo.identity is a git remote URL, or `local:<absolute path>` when there is no remote, which normally contains the account username. Sixteen unsalted hex characters over that input space is enumerable, so the hash was not a privacy control at all. Salted per install, with the salt kept in the identity file. That preserves every within-account join the analytics actually use and gives up only cross-machine joins on the same repository, which nothing computes. Since the distinct_id is already the email, the hash was never buying privacy from us — only from whoever obtains the data later, which is exactly what the salt fixes. Also corrects deepseek-plugin's README and source comment, which told readers ZAPIER and STRANDS were already in the backend's KNOWN_EVENT_SOURCES allowlist. Neither was. Adds a Telemetry section to docs/integrations/claude-code.mdx, which had none. Claude-Session: https://claude.ai/code/session_01C7tEmH86HAr7GoAAKCEHZb
4.7 KiB
mem0-strands
Persistent long-term memory for Strands Agents, backed by Mem0
A community Strands Agents integration that plugs
Mem0 in as a first-class MemoryStore.
mem0-strands gives Strands agents durable memory
that survives across sessions, backed by Mem0. Where the
mem0_memory tool is called explicitly by the model, Mem0MemoryStore plugs into the agent loop
directly: the manager recalls context and injects it automatically, and writes new memories, either
verbatim or by extracting facts from the conversation.
- Automatic recall + injection — relevant memories are searched and prepended to the prompt every turn, no tool call required.
- Server-side extraction — raw conversation turns are handed to Mem0, which distills and de-duplicates facts on its own pipeline (no extra client-side model call).
- Hosted or self-hosted — the managed Mem0 Platform by default, or your own Mem0 OSS backend via a config dict.
Install
pip install mem0-strands
Usage
from strands import Agent
from strands.memory import MemoryManager
from mem0_strands import Mem0MemoryStore
# Recall + write, distilling facts from the conversation via Mem0's server-side extraction.
store = Mem0MemoryStore(user_id="alex", writable=True, extraction=True)
agent = Agent(memory_manager=MemoryManager(stores=[store]))
# The agent now recalls from and writes to Mem0 without any explicit tool call.
agent("Remember that I prefer dark-mode dashboards and only drink oat milk.")
agent("How do I like my dashboards?") # recalls the stored preference
Set MEM0_API_KEY for the hosted platform (get one at app.mem0.ai), or pass
api_key=.... For a self-hosted Mem0 OSS backend, pass a config=... dict instead.
How it works
Mem0MemoryStore implements all three MemoryStore hooks:
| Method | Maps to | When it runs |
|---|---|---|
search(query) |
mem0.search(query, filters={...}) |
Every turn, to recall and inject context |
add(content) |
mem0.add(content, infer=False) |
The add_memory tool / a client-side extractor — stores a fact verbatim |
add_messages(messages) |
mem0.add(rendered_turns, infer=True) |
Extraction — renders conversation turns to text, then hands them to Mem0's server-side extraction |
Because add_messages is implemented, enabling extraction routes conversation turns straight to Mem0's own
extraction pipeline. A store that only implemented add would instead need a client-side ModelExtractor
(an extra model call) to distill facts first.
Configuration
| Argument | Default | Description |
|---|---|---|
user_id / agent_id / run_id / app_id |
(at least one required) | Mem0 entity scope that owns the memories |
name |
"mem0" |
Store identifier, used to target it from memory tools |
writable |
True |
Whether the manager may write to the store |
extraction |
None |
Automatic extraction (bool or ExtractionConfig) |
max_search_results |
None |
Default result cap per search (falls back to 5) |
metadata |
None |
Default metadata merged into every write |
api_key / host |
env | Mem0 platform key / base URL (api_key defaults to $MEM0_API_KEY) |
config |
None |
Mem0 OSS config dict for a self-hosted backend |
The explicit tool
For the model-called tool (store / retrieve / get / delete), use the
mem0_memory tool from strands-agents-tools. The store and
the tool share one Mem0 backend and namespace.
Telemetry
The store sends usage events (store configuration, operation, duration, result
counts, coarse failure kind) over the Mem0 SDK's existing telemetry client,
tagged source="STRANDS". These are not anonymous: when an API key is
configured they are sent under your Mem0 account email, the same way the SDK
attributes its own. Queries, memory text, message content, entity ids, and
metadata are never sent. Turn it off with MEM0_TELEMETRY=false.
Development
The package lives under python/ (monorepo-style layout matching the
Strands extension-template).
cd python
pip install hatch
hatch run test # pytest (no live server required — mocked client)
hatch run prepare # format + lint + typecheck + test
License
Apache-2.0. Mem0 is a trademark of its respective owner. Strands Agents is a project of its respective authors.