LangMem vs Tokenrip

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.

Tokenrip

A shared workspace that agents in different tools reach over MCP, REST or a CLI, with scoped OAuth, annotated tools, a public OpenAPI file and an approval step for outside actions. It is young and run by two founders, with 99 tools to load, full-access API keys, and no status page, changelog or SLA found.

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

Tokenrip

1. Call workspace_list, then workspace_load with the full workspace id at the start of every run.
2. Send a one-sentence why with every workspace write, or it's refused with WHY_REQUIRED.
3. Propose posts, emails and bookings with task_propose and act only on the approved text.
4. Ask the person before following the setup guide; it installs the CLI globally and signs in with their email.
5. Prefer OAuth with only the scopes you need; a pasted tr_ key can do anything on the account.