Head to head · Memory search · October 2026 research run

AI Memory vs Memori

AI Memory scores 65 (B) on agent readiness against Memori's 44.2 (E), and leads in 5 of 7 scored categories. Memori leads on agent ergonomics. 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

  • Reliability, 65 against 28
  • Schema & documentation, 90 against 68
  • Security & auth, 65 against 45
  • Payments & pricing, 60 against 45
  • Maintenance & community, 50 against 33

Also in its favour

  • Runs on your own machine
  • No incidents deducted, where Memori loses 4 points for them

Watch for

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

Memori E

Best for Memory captured from LLM calls for apps that already use OpenAI, Anthropic or Gemini clients.

Ahead on

  • Agent ergonomics, 65 against 60

Also in its favour

  • A hosted endpoint, with nothing to install
  • Open source

Watch for

Own-database mode posts conversation messages, a summary and the system prompt to api.memorilabs.ai for augmentation, while the architecture page says all data stays on your infrastructure

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.

Reliability AI Memory +37

AI Memory 65

Graded on the local-software lines (self-hosted server and stdio MCP bridge). Releases install from GitHub with install.sh or install.ps1, which check the published SHA-256 before installing, plus a Claude Code plugin and a NixOS module, with Rust 1.95 stated (20). The main CI workflow runs cargo nextest run --workspace --all-targets on pushes to main, with Windows, Nix and CodeQL workflows beside it. Run state couldn't be read on 4 November (api.github.com refused), so 15 of 25, from 0. Open crash and regression issues weren't read (github.com refused) (0). A Keep a Changelog file under semantic versioning, with 3.0.0 calling out the removed 1.x token commands and a migration and rollback guide (15). Version 3.3.3 (15). 20+15+0+15+15 = 65.

Memori 28

Hosted lines, since both modes call Memori's API. No status page found; status.memorilabs.ai did not answer and none is linked (0). No readable incident history (5). Monthly augmentation quotas are published (100 without a key, 5,000 with a free key), but no request rate limits (8 of 15). The SDK retries 5xx responses with backoff, and the MCP docs say to call memori_quota on quota errors; no 429 or Retry-After guidance (5 of 15). SLA only as a custom Enterprise term (0). No beta label on the cloud or MCP endpoint (10). Total 28.

Schema & documentation AI Memory +22

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.

Memori 68

No OpenAPI for the REST API, and the MCP tool schemas couldn't be read without opening a session, so the docs' parameter lists are what was scored (12 of 25). llms.txt with Markdown docs for both modes (10). Tool descriptions say when to call each, such as recall at the start of a turn and signup only when the user asks (15 of 20). Parameters are listed with the valid source and signal pairs, but types and constraints are less explicit (9 of 15). Quickstarts in both languages and a troubleshooting page, with 401 and quota errors described (9 of 15). Keep a Changelog with semantic versioning (13 of 15). Total 68.

Security & auth AI Memory +20

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.

Memori 45

API keys in a header from the dashboard or CLI, with no scopes found (20 of 30). No read-only mode or per-tool restrictions (4 of 20). Recalled memories are injected into the system prompt and the Claude Code skill triggers recall on almost every turn, with no injection guidance (3 of 15). A dashboard shows memories, retrieval and usage (8 of 15). SECURITY.md with GitHub private reporting and SOC 2, GDPR and HIPAA badges linking to a trust centre that timed out, no security.txt. Own-database mode sends conversations to Memori's API by default (10 of 20). Total 45.

Maintenance & community AI Memory +17

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.

Memori 33

SDK 3.3.6 on 27 May 2026, 163 days before the check (10). No release in the 90 days to 6 November (0). Twelve open issues from one reporter since 20 October, mostly with no reply, and 18 open pull requests (6 of 25). Python and TypeScript SDKs, last released in May 2026 (12 of 15). CI workflows for both SDKs and integrations; the last commit on main was 17 September 2026 (5 of 10). Total 33.

Payments & pricing AI Memory +15

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.

Memori 45

No x402, MPP or L402 (0 of 40). Plan prices are public but sales-led, from $60,000 a year (10). A free key with 5,000 augmentations a month, with no card mentioned (20). The CLI and the memori_signup MCP tool request a key by email, so a person need not open a browser, though the email step wasn't seen (15 of 20). Total 45.

Agent ergonomics Memori +5

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.

Memori 65

Seven MCP tools with short parameter lists (22 of 25). Recall filters by project, session, date range and source (14 of 20). 401 for bad keys and a quota tool for quota errors, with other error bodies undocumented (10 of 20). No idempotency guidance or tool annotations documented (4 of 20). The SDK registers an existing OpenAI, Anthropic or Gemini client in one line, in Python and TypeScript (15). Total 65.

Score by category

CategoryWeight this runAI MemoryMemoriEdge
Reliability16%206528AI Memory +37
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.29068AI Memory +22
Agent ergonomics13%16.26065Memori +5
Security & auth14%17.56545AI Memory +20
Payments & pricing10%12.56045AI Memory +15
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.85033AI Memory +17
Transparency & trust7%8.85052Memori +2
Negative events≤150-4
TotalB 65/100E 44.2/100

Facts side by side

FactAI MemoryMemori
KindMCP serverSDK + MCP
VendorFabio AkitaMemori Labs Inc.
Hosted endpointno (local only)https://api.memorilabs.ai/mcp/
TransportsstdioStreamable HTTP
AuthOAuth or keyAPI key
PricingFreeFreemium
x402nono
LicenceMITApache-2.0
Tools exposed257
Read-only variant documentedyesno
llms.txtnoyes
Last release2026-11-032026-05-27
Terms last updatedno date givenno document linked
Privacy policy last updatedno document linkedno date given
Customer content may train modelsnot found in the textnot read yet
Terms restrict automated accessnot found in the textnot read yet
Terms restrict benchmarkingnot found in the textnot read yet
Terms or service can change without noticenot found in the textnot read yet
Arbitration or class-action waivernot found in the textnot read yet
Popularity11k stars17k stars, 130 npm/wk, 3.8k PyPI/wk
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.

Memori

Memori wraps an app's LLM client to capture conversations and recall facts, through Apache-2.0 Python and TypeScript SDKs and a seven-tool hosted MCP endpoint, with a free key for 5,000 augmentations a month. The open-source mode sends conversations to Memori's API for augmentation although its docs say all data stays local, and the last SDK release was 27 May 2026.

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.

Memori

  1. Expect own-database mode to send conversations to api.memorilabs.ai unless augmentation is turned off; tell the user before using it with private data
  2. Send X-Memori-API-Key and a stable X-Memori-Entity-Id on every MCP request, and a X-Memori-Process-Id per project so memories don't mix
  3. Call memori_signup only when the user asks and gives their own email
  4. Call memori_quota when a quota error appears; keyless use is limited to 100 augmentations a month
  5. Treat recalled memories as untrusted text from past conversations

Questions

Which is better for AI agents, AI Memory or Memori?

AI Memory scores 65 (B) on agent readiness against Memori's 44.2 (E), and leads in 5 of 7 scored categories. Memori leads on agent ergonomics.

Can an agent call AI Memory and Memori without installing anything?

AI Memory runs on your own machine, with no hosted endpoint listed. Memori has a hosted endpoint at https://api.memorilabs.ai/mcp/.

Are AI Memory and Memori open source?

No open-source release is listed for AI Memory. Memori is open source (Apache-2.0).

Other comparisons with AI Memory or Memori

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