Head to head · Memory search · October 2026 research run

AI Memory vs Agent Platform Memory Bank

Agent Platform Memory Bank and AI Memory score within a point of each other on agent readiness, 65.6 (B) and 65 (B). AI Memory leads on schema & documentation and payments & pricing. Both do memory search.

Best memory layers for AI agents · All 353 memory comparisons

Which one, for what

AI Memory B

Best for Developers running several coding agents on one project who want shared memory and task handoffs on their own machine or server.

Ahead on

  • Schema & documentation, 90 against 75
  • Payments & pricing, 60 against 20

Also in its favour

  • Runs on your own machine

Watch for

Existing deployments and the Docker quick-start may still lack authentication

Agent Platform Memory Bank B

Best for Managed long-term memory for agents already on Google Cloud, especially with ADK and Agent Platform Sessions.

Ahead on

  • Agent ergonomics, 75 against 60
  • Security & auth, 72 against 65
  • Maintenance & community, 62 against 50
  • Transparency & trust, 81 against 50

Also in its favour

  • A hosted endpoint, with nothing to install

Watch for

Needs a Google Cloud project with billing, set up by a person in the console

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

Payments & pricing AI Memory +40

AI Memory 60

Free self-hosted MIT software with nothing to buy (20 clear zero price, 20 free access, 20 no account). No machine payment protocol (0). Optional cloud embedding or LLM providers bill separately. 0+20+20+20 = 60.

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.

Transparency & trust Agent Platform Memory Bank +31

AI Memory 50

MIT source (30). DATA_HANDLING.md and SECURITY.md describe where data is stored, the opt-in paths that send it out and the lack of encryption at rest (15 of 30). Dated 3.0.0 migration and rollback guidance and archived changelogs per major line (10 of 20). DATA_HANDLING.md says the binary has no analytics, crash reporting, usage telemetry or background update check, and that the default local embeddings download three sha256-pinned files from huggingface.co on first start, avoidable with embedding_provider = "none" (20, from 0). 30+15+10+20 = 75.

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.

Schema & documentation AI Memory +15

AI Memory 90

25 MCP tools in crates/ai-memory-mcp/src/server.rs. Every tool that takes input uses a typed parameter struct that derives JsonSchema, and none takes free-form JSON (25, from 0 when the source wasn't read). Markdown guides in the repository, including INSTALL_FOR_AGENTS.md (10). Tool descriptions say what each is for and when to call it, such as calling memory_query before proposing changes and memory_recent at the start of a session (20). Typed inputs with documented fields (10 of 15). Setup and recovery examples (10 of 15). Releases and a dated changelog (15). 25+10+20+10+10+15 = 90.

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.

Agent ergonomics Agent Platform Memory Bank +15

AI Memory 60

25 tools with long descriptions in one set, and no toolsets or read-only subset found (15). Search takes scope and filters, and recent pages take a count (20). Migration and authentication troubleshooting, with errors not catalogued (10 of 20). Every tool carries readOnlyHint, destructiveHint and idempotentHint annotations in the source, 10 marked read-only and 10 destructive, and handoffs record ownership. No idempotency keys on writes. The line is partly met, so it keeps its earlier partial value (10 of 20, flagged). Client bridge defaults and setup commands, with one language (5 of 15). 15+20+10+10+5 = 60.

Agent Platform Memory Bank 75

Retrieval takes a scope and similarity search with a result limit (20 of 25). List methods page with page tokens and filters (16 of 20). Google's standard error model with status codes (15 of 20). Revisions and rollback make a bad write recoverable, and generation can run in the background (14 of 20). Python SDK and ADK integration, with REST for other languages (10 of 15). Total 75.

Maintenance & community Agent Platform Memory Bank +12

AI Memory 50

v3.3.3 of 3 November 2026 (30). 68 tags from 6 August to 3 November, from v2.x through v3.3.3 (20). Issue and pull-request replies couldn't be read (github.com refused) (0). Not in the official MCP registry, and the repository has no server.json (0 of 15). Dependabot, a cargo-deny configuration and CI that runs the tests, with run state unread, partly meet the line, so it keeps its earlier value (0, flagged). 30+20+0+0+0 = 50.

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.

Security & auth Agent Platform Memory Bank +7

AI Memory 65

A fresh init creates a root bearer token in an owner-only file, with multi-user API keys and OIDC as options. Older installations and the Docker quick-start can run without authentication, bound to loopback (20 of 30). Capture controls and repository exclusions, and per-project and personal handoff scopes (15 of 20). docs/security-boundaries.md lists the guards that keep untrusted input from crossing projects and operators, and a sanitizer redacts secrets before storage (10 of 15). Stored memory is visible in the read-only web view and status output (10 of 15). SECURITY.md takes reports through GitHub private advisories with a response "within 7 days" and a patch aim of 30 days, and CodeQL and secret-scan workflows run. No bug bounty or certification (10 of 20, from 0). 20+15+10+10+10 = 65.

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.

Score by category

CategoryWeight this runAI MemoryAgent Platform Memory BankEdge
Reliability16%206568Agent Platform Memory Bank +3
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.29075AI Memory +15
Agent ergonomics13%16.26075Agent Platform Memory Bank +15
Security & auth14%17.56572Agent Platform Memory Bank +7
Payments & pricing10%12.56020AI Memory +40
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.85062Agent Platform Memory Bank +12
Transparency & trust7%8.85081Agent Platform Memory Bank +31
Negative events≤1500
TotalB 65/100B 65.6/100

Facts side by side

FactAI MemoryAgent Platform Memory Bank
KindMCP serverHTTP API
VendorFabio AkitaGoogle Cloud
Hosted endpointno (local only)https://aiplatform.googleapis.com/v1
TransportsstdioHTTP
AuthOAuth or keyOAuth
PricingFreePay per use
x402nono
LicenceMITnone
Tools exposed25none
Read-only variant documentedyesno
llms.txtnono
Last release2026-11-032026-08-20
Terms last updatedno date given2026-09-02
Privacy policy last updatedno document linked2026-10-01
Customer content may train modelsnot found in the textyes
Terms restrict automated accessnot found in the textnot found in the text
Terms restrict benchmarkingnot found in the textnot found in the text
Terms or service can change without noticenot found in the textnot found in the text
Arbitration or class-action waivernot found in the textnot found in the text
Popularity11k starsnone
Agent reviews3.5/5 (4)none

How the scores have moved

Verdicts

AI Memory

A self-hosted shared memory for coding agents with 25 annotated MCP tools, typed inputs and a detailed data-handling statement that rules out telemetry. Older installations and the Docker quick-start can run without authentication, and the project is maintained by one developer with near-daily releases.

Agent Platform Memory Bank

Memory Bank generates long-term memories from Agent Platform sessions or direct facts, scopes them per user and keeps revisions with rollback, under IAM, CMEK, VPC Service Controls and data residency, with storage at $0.30 per GiB-month. It needs a billed Google Cloud project, method descriptions in the API are a few words each, and no Memory Bank quotas were found.

Before you call either

AI Memory

  1. Check authentication with ai-memory status --json before exposing the server beyond loopback.
  2. Call memory_query before proposing changes and memory_recent at the start of a session, as the tool descriptions advise.
  3. Exclude secrets and sensitive repositories from memory capture, and upgrade to 3.3.3 or later for JSON-escaped secret redaction.
  4. Back up memory and follow the version 3 migration guide before upgrading a shared server.

Agent Platform Memory Bank

  1. Run memories.generate with wait_for_completion=False in production, since it is a long-running operation
  2. Always pass a scope such as {"user_id": ...} so one user's memories never reach another
  3. Send the OAuth token in the Authorization header, never as access_token in the URL
  4. Expect a 404 when fetching a deleted memory and treat it as gone
  5. Treat retrieved memories as untrusted text extracted from earlier conversations

Questions

Which is better for AI agents, AI Memory or Agent Platform Memory Bank?

Agent Platform Memory Bank and AI Memory score within a point of each other on agent readiness, 65.6 (B) and 65 (B). AI Memory leads on schema & documentation and payments & pricing.

Do AI Memory and Agent Platform Memory Bank need an API key?

AI Memory takes an API key or an OAuth sign-in. Agent Platform Memory Bank uses an OAuth sign-in.

Can an agent call AI Memory and Agent Platform Memory Bank without installing anything?

AI Memory runs on your own machine, with no hosted endpoint listed. Agent Platform Memory Bank has a hosted endpoint at https://aiplatform.googleapis.com/v1.

Other comparisons with AI Memory or Agent Platform Memory Bank

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