Agent Platform Memory Bank vs LangMem

Agent Platform Memory Bank 62

The newest Memory Bank release notes are of 20 August 2026 (IngestEvents GA, metadata, Gemini Embedding 2), 78 days before the check, and billing started on 1 September (20). Three Memory Bank entries in the 90 days, all on 20 August (10 of 20). Public release notes and Cloud Customer Care (12 of 15). google-cloud-agentplatform 2.7.0 on 28 October 2026, twelve releases in 90 days per its PyPI release feed, plus ADK (15). SDK test status not checked (5 of 10). Total 62.

LangMem 15

No release found in the last 180 days. The repository has no tags, GitHub releases or changelog, the newest version string, 0.0.30, was set in pyproject.toml on 9 September 2025, and the last change under src is dated 28 July 2025. PyPI's release dates could not be read on 4 November (0). No release in the last 90 days (0). Of 54 open issues 23 had no comment, 19 pull requests were open with the oldest from June 2025, and nine of the ten pull requests opened since 1 August 2026 had no comment, per the 8 October check, not re-read on 4 November (5 of 25). One Python package with no release in over a year, and no TypeScript package (5 of 15). Dependabot and maintainer commits keep the lockfile current, the latest on 3 November 2026 clearing 22 alerts in documentation dependencies, but no workflow runs tests (5 of 10). 0+0+5+5+5 = 15.

Agent Platform Memory Bank 20

No x402, MPP or L402 (0). Storage, read and write prices are published without a login (20). No Memory Bank free tier found (0). A person creates the project, enables billing and sets up IAM in the console (0). Total 20.

LangMem 60

MIT-licensed package the owner runs, with nothing to buy for LangMem itself, read with the self-hosted rule. 20 for pricing, 20 for a free start and 20 for use without an account. No x402, MPP or L402 in the docs or source (0). LLM, embedding and database costs are the owner's.

Agent Platform Memory Bank 68

Hosted lines. Google Cloud status dashboard with per-product history (20). Its incident feed, read on 6 November 2026, holds four incidents since 8 August (20 August, 27 products; 1 September, us-central1-b; 8 October, Cloud Storage; 20 October, europe-west2, 38 products), and none names Agent Platform, Vertex or Memory Bank (30). No Memory Bank quotas or rate limits were found; the platform quotas path guessed returned 404 (0, unchecked). Generation is a long-running operation with wait and cancel methods, and Google's retry guidance wasn't re-read for this API (8 of 15). No SLA for Memory Bank was found in the pages read (0, unchecked). Memory profiles, IngestEvents and multi-regional endpoints are GA (10). Total 68.

LangMem 32

Local-software reading. Installs from PyPI as langmem with Python 3.10 or later declared, but extraction.py on main uses typing.NotRequired, which arrived in Python 3.11, and issues 81 and 83 about failed imports on 3.10 are open (per the 8 October check). We read the source and did not run it on 3.10 (14 of 20). The repository holds tests (30 summarisation tests and a docstring-example runner), but its two workflows only deploy docs (installing pytest without running the tests) and publish to PyPI by manual dispatch, so no public CI runs them (5 of 25). 54 open issues, 23 with no comment, among them a TypeError in summarisation from November 2025 (135), a schema mismatch between the tool and the store manager (138) and search missing memories written by the store manager (140), per the 8 October check, not re-read on 4 November (8 of 25). Versions are 0.0.x with no changelog, GitHub releases or tags, and open issue 130 shows 0.0.30 was cut to restore compatibility with LangGraph 1.0 (5 of 15). Below 1.0 and not declared stable (0). 14+5+8+5+0 = 32.

Agent Platform Memory Bank 72

OAuth 2.0 with IAM and service accounts (30), less 10, as for the other Google API listings, because the v1 discovery document lists access_token, oauth_token and key as query parameters (20 of 30). IAM Conditions can restrict access by memory scope; purge and delete have no confirmation (15 of 20). Memories are written by an LLM from conversation content and returned to agents, with no injection guidance found (5 of 15). Access Transparency and Access Approval are listed; Cloud Audit Logs coverage for Memory Bank wasn't read (12 of 15). Google's valid security.txt, vulnerability reward programme and certifications, with HIPAA listed for Memory Bank (20). Total 72.

LangMem 42

Local-software reading. The library holds no credential of its own and opens no port. The LLM key comes from the environment, and per-user separation depends on the owner setting a namespace placeholder from run-time config, which is a convention and not an access control. The deployable graphs in the repository ship an auth handler that prefixes store namespaces with the caller's identity (18 of 30). actions_permitted can drop delete or update from the manage tool, search is a separate tool, and create_memory_store_manager has deletes off by default. Nothing asks for confirmation before a delete (14 of 20). Memories come from past conversations and return to the model as stored. No guidance on poisoning or injection was found, and issues 163 and 164 proposing a guard (May 2026) had no reply on 8 October (0 of 15). No audit log in the library. Store items carry created and updated timestamps (3 of 15). LangChain's organisation SECURITY.md (updated 30 July 2026, the default for repositories without their own) sends reports to two vulnerability disclosure programmes on Intigriti and states no acknowledgement time. No SECURITY.md in this repository, no bounty named, no security.txt on langchain.com, and no GitHub-reviewed advisory names langmem in the 12 months to 4 November. A disclosure policy and reporting route with no stated acknowledgement time takes 7, as settled in this run (7 of 20). 18+14+0+3+7 = 42.

Agent Platform Memory Bank 75

Google's discovery document is a machine-readable contract for every memory method (25). No llms.txt or Markdown docs found (0). Method descriptions are 13 to 39 characters, one-line summaries, while the guides explain when to generate from sessions or from direct facts (12 of 20). Typed schemas with required fields in the discovery document (12 of 15). Python examples, a troubleshooting page and a documented 404 for deleted memories (11 of 15). v1 and v1beta1 and dated release notes (15). Total 75.

LangMem 55

Library reading, with the tool lines applied to the two agent tools. No OpenAPI applies. Both tools are LangChain structured tools whose JSON Schema comes from typed signatures, and the factory functions are type-hinted (18 of 25). langchain-ai.github.io/langmem/llms.txt returns 404 (0). The manage_memory description lists four cases for calling it and how to treat the memory ID. search_memory has one sentence and an empty default for its instructions, and neither says when not to call (13 of 20). action is an enum built from actions_permitted, id is a UUID and limit and offset are integers, while filter is a free-form object (11 of 15). Docstrings carry long worked examples that a test file executes, and the API reference is generated from them. Error behaviour is not documented (10 of 15). Version numbers exist only on PyPI, with no changelog (3 of 15).

Agent Platform Memory Bank 81

Closed service under the Google Cloud terms (15). Data residency at rest, CMEK and the Cloud Data Processing Addendum apply; no Memory Bank retention period or time-to-live was read (20 of 30). The rename was announced in the release notes with old and new names listed, and Google's deprecation policy covers GA services (14 of 20). Google Cloud's subprocessor list and regional endpoints are published (16 of 20). Total 65.

LangMem 63

MIT licence in the repository and on PyPI (30). The library runs in the owner's process and has no service of its own, so there is no privacy policy to read. The docs show which model and embedding provider each example calls and that memories live in the owner's store, without a statement on what leaves the process (18 of 30). No deprecation policy or dated notices were found (0 of 20). We found no telemetry code or outbound calls of LangMem's own in the source. Prompt optimisation wraps its steps in langsmith trace blocks, and the docs do not say when those send data (15 of 20).