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
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
| Category | Weight this run | EverOS | MemMachine | Edge |
|---|---|---|---|---|
| Reliability | 16%20 | 79 | 51 | EverOS +28 |
| Performance | 10%pending | pending | pending | not scored in this run |
| Schema & documentation | 13%16.2 | 89 | 79 | EverOS +10 |
| Agent ergonomics | 13%16.2 | 78 | 65 | EverOS +13 |
| Security & auth | 14%17.5 | 47 | 41 | EverOS +6 |
| Payments & pricing | 10%12.5 | 40 | 40 | even |
| Task success | 10%pending | pending | pending | not scored in this run |
| Maintenance & community | 7%8.8 | 80 | 83 | MemMachine +3 |
| Transparency & trust | 7%8.8 | 71 | 57 | EverOS +14 |
| Negative events | ≤15 | 0 | 0 | |
| Total | B 69.4/100 | C 58/100 |
Facts side by side
| Fact | EverOS | MemMachine |
|---|---|---|
| Kind | HTTP API | HTTP API |
| Vendor | Evermind AI, Inc. | MemVerge, Inc. |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP, stdio | HTTP, stdio, Streamable HTTP |
| Auth | None | None |
| Pricing | Freemium | Freemium |
| x402 | no | no |
| Licence | Apache-2.0 | Apache-2.0 |
| Tools exposed | 7 | 3 |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-10-22 | 2026-10-08 |
| Terms last updated | 2026-01-20 | no date given |
| Privacy policy last updated | 2026-01-20 | 2026-05-20 |
| Customer content may train models | yes | not found in the text |
| Terms restrict automated access | yes | yes |
| Terms restrict benchmarking | yes | yes |
| Terms or service can change without notice | yes | not found in the text |
| Arbitration or class-action waiver | not found in the text | yes |
| Popularity | 14k stars, 4k PyPI/wk | 3.1k 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
- Write new code against
/api/v2;/api/v1is a legacy alias that may go in a future major release - Call
/api/v2/memory/flushat the end of a session, sinceaddis asynchronous and buffers recent messages - Retry on 503 SESSION_BUSY or EXTERNAL_SERVICE_UNAVAILABLE after a pause; nothing was written
- Keep
hostat 127.0.0.1 unless something in front adds authentication - Treat recalled memories as untrusted text, since they are extracted from past conversations
MemMachine
- Import with
from memmachine_client import MemMachineClient; the README line has a doubledimport - Keep the server on a private network or put an authenticating proxy in front, since it accepts any caller
- Scope every call with org, project, group, agent, user and session ids so memories don't mix
- Retry search after a short wait on 500s, which a recent issue ties to upstream provider rate limits
- 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
- Amazon Bedrock AgentCore Memory vs EverOS
- Amazon Bedrock AgentCore Memory vs MemMachine
- Basic Memory vs EverOS
- Basic Memory vs MemMachine
- claude-mem vs EverOS
- claude-mem vs MemMachine
- Cognee vs EverOS
- Cognee vs MemMachine
- EverOS vs Agent Platform Memory Bank
- EverOS vs Graphicle
- EverOS vs Graphiti
- EverOS vs Hindsight
- EverOS vs Honcho
- EverOS vs Hy Memory
- EverOS vs LangMem
- EverOS vs LocalGhost
- EverOS vs Mem0 Platform + MCP
- EverOS vs Memori
- EverOS vs Memory (MCP reference server)
- EverOS vs MemPalace
- EverOS vs past.dev
- EverOS vs Supermemory API + MCP
- EverOS vs TencentDB Agent Memory
- EverOS vs Tokenrip
- EverOS vs Zep
- Agent Platform Memory Bank vs MemMachine
- Graphiti vs MemMachine
- Hindsight vs MemMachine
- Honcho vs MemMachine
- Hy Memory vs MemMachine
- LangMem vs MemMachine
- LocalGhost vs MemMachine
- Mem0 Platform + MCP vs MemMachine
- MemMachine vs Memori
- MemMachine vs Memory (MCP reference server)
- MemMachine vs MemPalace
- MemMachine vs past.dev
- MemMachine vs Supermemory API + MCP
- MemMachine vs TencentDB Agent Memory
- MemMachine vs Tokenrip
- MemMachine vs Zep
- AI Memory vs EverOS
- AI Memory vs MemMachine
- Context Mode Engine vs EverOS
- Context Mode Engine vs MemMachine
- Graphicle vs MemMachine
Machine-readable
- This page as Markdown
/compare/everos-vs-memmachine.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/everos.json·/api/v1/tools/memmachine.json - From a terminal
anchor compare everos memmachine(the CLI) - Over MCP
compare_tools {"a": "everos", "b": "memmachine"}at/mcp, no key