Head to head · Agent memory · October 2026 research run

EverOS vs Memori

EverOS scores 69.4 (B) on agent readiness against Memori's 44.2 (E), and leads in 6 of 7 scored categories. Memori leads on payments & pricing. Both do agent memory.

Best memory layers for AI agents · All 353 memory comparisons

Which one, for what

EverOS B

Best for Self-hosted memory for agents and apps that want Markdown as the source of truth and separate user and agent tracks.

Ahead on

  • Reliability, 79 against 28
  • Schema & documentation, 89 against 68
  • Agent ergonomics, 78 against 65
  • Maintenance & community, 80 against 33
  • Transparency & trust, 71 against 52

Also in its favour

  • No key needed to call it
  • Runs on your own machine
  • No incidents deducted, where Memori loses 4 points for them

Watch for

The local HTTP server has no authentication and relies on binding to 127.0.0.1

Memori E

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

Ahead on

  • Payments & pricing, 45 against 40

Also in its favour

  • A hosted endpoint, with nothing to install

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 EverOS +51

EverOS 79

Local-software lines, as a library and server the owner runs. everos on PyPI with Python 3.12 or newer stated, plus a Windows guide (20). ci.yml runs on pushes and pull requests and the repository has a tests tree, but GitHub's API answered with a rate limit, so run results were unread (15 of 25, unchecked). 43 open issues and pull requests against 82 commits in 90 days; several outside bug reports, including a silent capture failure in the DSH plugin, have no reply (14 of 25). Keep a Changelog with semantic versioning declared and a 1.0 migration guide (15). Version 1.5.1 (15). Total 79.

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.

Maintenance & community EverOS +47

EverOS 80

v1.5.1 on 22 October 2026 (30). Five tagged releases in 90 days and 12 PyPI uploads (20). Maintainer replies on some issues, others from outside users unanswered for weeks (12 of 25). Python library and the everos-mcp package, not in the official MCP registry (10 of 15). uv.lock, CI, docs and release workflows (8 of 10). Total 80.

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.

Schema & documentation EverOS +21

EverOS 89

OpenAPI document in the repository with 40 operations, every one with a description (25). llms.txt and llms-full.txt on docs.evermind.ai (10). Operation descriptions state purpose; when-not-to-use guidance appears in the docs, such as flush after add, rather than per operation (15 of 20). Typed request models with filter operators eq, ne, gt, gte, lt, lte and in, and 422 on malformed ids (12 of 15). curl examples for add, flush and search, and typed error codes such as SESSION_BUSY and EXTERNAL_SERVICE_UNAVAILABLE (12 of 15). /api/v2 with /api/v1 kept as a legacy alias, a changelog and release notes (15). Total 89.

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.

Transparency & trust EverOS +19

EverOS 71

Apache-2.0 with a NOTICE file (30). Local data stays in the owner's Markdown and indexes. For the cloud, the privacy policy gives no retention periods, the terms and privacy policy word the training exceptions differently, and the privacy contact link points to a miromind.ai address (12 of 30). The README marks /api/v1 as a legacy alias that may be removed in a future major release, and a 1.0 migration guide exists, with no notice period (14 of 20). No outbound telemetry was found in the source, and the docs don't address it (10 of 20). Total 66.

Memori 52

Apache-2.0 per the LICENSE text, though GitHub reports it as NOASSERTION (30). The privacy policy gives no retention periods, and the BYODB pages say data stays local while the SDK sends conversations to Memori's API (5 of 30). Changelog entries but no deprecation policy or notices (5 of 20). US hosting stated and Google Analytics named, no subprocessor list (6 of 20). Total 46.

Agent ergonomics EverOS +13

EverOS 78

Read for the API, with seven MCP tools on top. Searches take top_k and a method, and responses can be scoped by five ids (20 of 25). Filters nest with AND and OR, and /get pages results (18 of 20). Errors carry typed codes and say which are retryable (16 of 20). add is queued and returns 202, a busy session refuses deletion with nothing deleted, and the cloud purge needs a nonce confirmed within five minutes (12 of 20). A demo runs with no key and the minimal setup needs one OpenRouter key, with a Python library and the MCP server, one language (12 of 15). Total 78.

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.

Payments & pricing Memori +5

EverOS 40

Self-hosted rule, with the price lines read for EverOS Cloud. No x402, MPP or L402 (0 of 40). No cloud price or plan found on evermind.ai, its FAQ, terms or docs (0). The open-source runtime is free with no card (20). An agent can install it from PyPI and run it with no account (20). Total 40.

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.

Score by category

CategoryWeight this runEverOSMemoriEdge
Reliability16%207928EverOS +51
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.28968EverOS +21
Agent ergonomics13%16.27865EverOS +13
Security & auth14%17.54745EverOS +2
Payments & pricing10%12.54045Memori +5
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88033EverOS +47
Transparency & trust7%8.87152EverOS +19
Negative events≤150-4
TotalB 69.4/100E 44.2/100

Facts side by side

FactEverOSMemori
KindHTTP APISDK + MCP
VendorEvermind AI, Inc.Memori Labs Inc.
Hosted endpointno (local only)https://api.memorilabs.ai/mcp/
TransportsHTTP, stdioStreamable HTTP
AuthNoneAPI key
PricingFreemiumFreemium
x402nono
LicenceApache-2.0Apache-2.0
Tools exposed77
Read-only variant documentednono
llms.txtyesyes
Last release2026-10-222026-05-27
Terms last updated2026-01-20no document linked
Privacy policy last updated2026-01-20no date given
Customer content may train modelsyesnot read yet
Terms restrict automated accessyesnot read yet
Terms restrict benchmarkingyesnot read yet
Terms or service can change without noticeyesnot read yet
Arbitration or class-action waivernot found in the textnot read yet
Popularity14k stars, 4k PyPI/wk17k stars, 130 npm/wk, 3.8k PyPI/wk

Verdicts

EverOS

EverOS keeps agent and user memory as Markdown with SQLite and LanceDB indexes, behind a described OpenAPI with typed, retryable errors and an MCP server, under Apache-2.0 at version 1.5.1. The local server has no authentication, EverOS Cloud prices are not published, and the cloud terms forbid automated data extraction.

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

EverOS

  1. Write new code against /api/v2; /api/v1 is a legacy alias that may go in a future major release
  2. Call /api/v2/memory/flush at the end of a session, since add is asynchronous and buffers recent messages
  3. Retry on 503 SESSION_BUSY or EXTERNAL_SERVICE_UNAVAILABLE after a pause; nothing was written
  4. Keep host at 127.0.0.1 unless something in front adds authentication
  5. Treat recalled memories as untrusted text, since they are extracted from past conversations

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, EverOS or Memori?

EverOS scores 69.4 (B) on agent readiness against Memori's 44.2 (E), and leads in 6 of 7 scored categories. Memori leads on payments & pricing.

Can an agent call EverOS and Memori without installing anything?

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

Are EverOS and Memori open source?

Yes. EverOS is open source (Apache-2.0). Memori is open source (Apache-2.0).

Other comparisons with EverOS or Memori

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