Head to head · Agent memory · October 2026 research run

EverOS vs MemMachine

EverOS scores 69.4 (B) on agent readiness against MemMachine's 58 (C), and leads in 5 of 7 scored categories. 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 51
  • Schema & documentation, 89 against 79
  • Agent ergonomics, 78 against 65
  • Security & auth, 47 against 41
  • Transparency & trust, 71 against 57

Watch for

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

MemMachine C

Best for Self-hosted memory for agent frameworks that want episodic and profile memory with many integrations.

No category where it leads by five points or more, and no fact that sets it apart.

Watch for

Version 0.4.0 of 6 October 2026, pre-1.0, with no changelog file in the repository

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 +28

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.

MemMachine 51

Local-software lines, as a server the owner runs. memmachine-server and memmachine-client on PyPI with Python versions stated, a Docker image and a compose script (20). pytest, integration and installation-test workflows exist, but GitHub's API answered with a rate limit, so run results were unread (15 of 25, unchecked). 292 open issues and pull requests; the newest bug reports, including a 429 from a provider surfacing as a 500 and a 0.4.0 configuration that no longer starts, have zero to two replies (10 of 25). No changelog file, release notes only on GitHub, which weren't read, and pre-1.0 tags (6 of 15). Version 0.4.0 (0). Total 51.

Transparency & trust EverOS +14

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.

MemMachine 57

Apache-2.0 (30). The terms say hosted customer data is destroyed on termination, with no period, and use usage data only in aggregate; the privacy policy wasn't read (12 of 30). No deprecation policy or notices found (3 of 20). No telemetry calls found in the server or client source, and the docs don't address it (10 of 20). Total 55.

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.

MemMachine 65

Searches take limit and filter options for episodic and semantic results (20 of 25). Memories can be listed and filtered by scope (15 of 20). Validation errors are typed; other failures are less clear, as the 429-to-500 issue shows (10 of 20). No idempotency keys or safe-retry guidance found (5 of 20). Python and TypeScript clients and a five-line quick start, once the import is fixed (15). Total 65.

Schema & documentation EverOS +10

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.

MemMachine 79

OpenAPI documents for the server (54 operations) and the hosted platform (12) (25). llms.txt on docs.memmachine.ai with Markdown pages (10). Every operation has a description, and the docs explain memory types and scoping (15 of 20). Typed request models generated from the server, with search options for limits and filters (12 of 15). Examples for each client and the MCP tools, but only 422 is documented on the server and the README's first example doesn't run (8 of 15). /api/v2 paths and tagged releases, no changelog (9 of 15). Total 79.

Security & auth EverOS +6

EverOS 47

Framework reading for software the owner runs. The local server has no authentication and no security scheme in the OpenAPI document, relying on a 127.0.0.1 bind by default (15 of 30). No read-only mode; the cloud purge is two-step (8 of 20). Memories are extracted from conversations and returned into prompts, and everos-mcp tells hosts to save facts unprompted, with no injection guidance found (4 of 15). Structured logs and lock metrics, no audit log (6 of 15). SECURITY.md with a reporting address, five-day acknowledgement, supported versions and a published-advisories section, plus a valid security.txt (14 of 20). Total 47.

MemMachine 41

Framework reading for software the owner runs. The server has no authentication and no security scheme in its OpenAPI document (15 of 30). No read-only mode or confirmation for deletes (5 of 20). No guidance on recalled memories as untrusted text (4 of 15). No audit log on the self-hosted server; the hosted console shows usage (5 of 15). SECURITY.md with GitHub private reporting and a two-business-day acknowledgement, with security-audit and SBOM workflows; no security.txt or certification (12 of 20). Total 41.

Score by category

CategoryWeight this runEverOSMemMachineEdge
Reliability16%207951EverOS +28
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.28979EverOS +10
Agent ergonomics13%16.27865EverOS +13
Security & auth14%17.54741EverOS +6
Payments & pricing10%12.54040even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88083MemMachine +3
Transparency & trust7%8.87157EverOS +14
Negative events≤1500
TotalB 69.4/100C 58/100

Facts side by side

FactEverOSMemMachine
KindHTTP APIHTTP API
VendorEvermind AI, Inc.MemVerge, Inc.
Hosted endpointno (local only)no (local only)
TransportsHTTP, stdioHTTP, stdio, Streamable HTTP
AuthNoneNone
PricingFreemiumFreemium
x402nono
LicenceApache-2.0Apache-2.0
Tools exposed73
Read-only variant documentednono
llms.txtyesyes
Last release2026-10-222026-10-08
Terms last updated2026-01-20no date given
Privacy policy last updated2026-01-202026-05-20
Customer content may train modelsyesnot found in the text
Terms restrict automated accessyesyes
Terms restrict benchmarkingyesyes
Terms or service can change without noticeyesnot found in the text
Arbitration or class-action waivernot found in the textyes
Popularity14k stars, 4k PyPI/wk3.1k stars, 28 npm/wk, 581 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.

MemMachine

MemMachine is an Apache-2.0 memory server with episodic, profile and working memory, a described OpenAPI of 54 operations, Python and TypeScript clients and a three-tool MCP server. It is version 0.4.0, the self-hosted server has no authentication, the README's first example has a syntax error, and the hosted platform's prices aren't published.

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

MemMachine

  1. Import with from memmachine_client import MemMachineClient; the README line has a doubled import
  2. Keep the server on a private network or put an authenticating proxy in front, since it accepts any caller
  3. Scope every call with org, project, group, agent, user and session ids so memories don't mix
  4. Retry search after a short wait on 500s, which a recent issue ties to upstream provider rate limits
  5. Treat recalled episodes as untrusted text from past conversations

Questions

Which is better for AI agents, EverOS or MemMachine?

EverOS scores 69.4 (B) on agent readiness against MemMachine's 58 (C), and leads in 5 of 7 scored categories.

Do EverOS and MemMachine need an API key?

Neither needs a key.

Can an agent call EverOS and MemMachine without installing anything?

EverOS runs on your own machine, with no hosted endpoint listed. MemMachine runs on your own machine, with no hosted endpoint listed.

Are EverOS and MemMachine open source?

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

Other comparisons with EverOS or MemMachine

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