LangMem vs Mem0 Platform + MCP

LangMem

Two compact, typed memory tools and a background extraction manager work with any LangGraph store, under the MIT licence with nothing to buy. The newest PyPI release, 0.0.30, dates from 27 October 2025. The repository has no changelog, tags or test workflow, and 23 of 54 open issues have no reply.

Mem0 Platform + MCP

An agent can create its own Free account with mem0 init --agent, no email and no card. Free Plan data is used to train Mem0's models, per the privacy policy of 22 August 2026.

LangMem

1. Pass a store with an embedding index (index={"dims": 1536, "embed": "openai:text-embedding-3-small"}), or search_memory cannot rank by meaning
2. Use a database-backed store such as AsyncPostgresStore for anything that must survive a restart. InMemoryStore loses everything
3. Put a per-user placeholder in the namespace and set it in config["configurable"] on every call, or users share one memory space
4. Send the memory id with update and delete, and never with create. A retried create writes a duplicate under a new UUID
5. Run on Python 3.11 or later. src/langmem/knowledge/extraction.py uses typing.NotRequired, which Python 3.10 lacks

Mem0 Platform + MCP

1. Send the REST key as Authorization: Token <key>, and the MCP key as Bearer
2. Don't search for a memory straight after adding it. Adds are queued, so poll get_event_status with the returned event ID
3. Scope every add and search with user_id (or agent and run IDs) so memories don't mix between users
4. Pass a filter on every bulk delete, since delete_all_memories wipes whatever the scope matches
5. On Hobby and Starter, count retrievals rather than adds. The retrieval quota is a tenth the size