# EverOS vs Mem0 Platform + MCP

> EverOS scores 69.4 (B) to Mem0 Platform's 40.1 (E) for agent memory. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/everos-vs-mem0
- Markdown: https://www.anchorterminal.com/compare/everos-vs-mem0.md (~4,750 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-07

EverOS scores 69.4 (B) on agent readiness against Mem0 Platform + MCP's 40.1 (E), and leads in 6 of 7 scored categories. Both do agent memory.

- EverOS: grade B, 69.4/100, rank #247 of 1510. Markdown https://www.anchorterminal.com/tools/everos.md · JSON https://www.anchorterminal.com/api/v1/tools/everos.json
- Mem0 Platform + MCP: grade E, 40.1/100, rank #1328 of 1510. Markdown https://www.anchorterminal.com/tools/mem0.md · JSON https://www.anchorterminal.com/api/v1/tools/mem0.json
- Best memory layers for AI agents: https://www.anchorterminal.com/best/agent-memory/index.md
- All 353 memory comparisons: https://www.anchorterminal.com/compare/agent-memory/index.md

## Which one, for what

### EverOS (B)

Good 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 25
- Schema & documentation, 89 against 80
- Agent ergonomics, 78 against 63
- Maintenance & community, 80 against 75
- Transparency & trust, 71 against 62

Also in its favour:
- No key needed to call it
- Runs on your own machine
- No incidents deducted, where Mem0 Platform + MCP loses 13 points for them

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

### Mem0 Platform + MCP (E)

Good for: Chat products that want per-user facts back with one search call and little setup, and teams willing to connect their own LLM key for higher free limits.

Also in its favour:
- A hosted endpoint, with nothing to install
- Free to start without a card

Watch for: Free Plan data is used to train Mem0's models, per the privacy policy of 22 August 2026


## Why the edge

### Reliability: EverOS +54

- 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.
- Mem0 Platform + MCP (25): A status page exists at status.mem0.ai. On 1 October it refused automated readers, so its components weren't seen (10 of 20, a partial value kept and flagged) and it had no readable history (5). Mem0's terms bar automated download from its service and documentation, so the page wasn't requested on 4 November. No Platform rate limits with numbers. The docs say only "Managed quotas per workspace" (0). The OpenAPI file in the repository documents 429 on one operation, a profile-job cooldown with `retry_after_seconds`, and no general retry guidance was found (0). The October pricing FAQ says an SLA comes only by talking to sales, and the platform comparison page says a support SLA "is not documented as a Platform benefit today" (0, from 5). The v3 API and the hosted MCP server are generally available (10). 10+5+0+0+0+10 = 25.

### Agent ergonomics: EverOS +15

- 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.
- Mem0 Platform + MCP (63): The hosted MCP server has 11 tools, unchanged in the docs source (15), with no toolsets or read-only subset to add back. Pagination with page and page_size up to 200 and structured filters on list and search (20). Errors are thin. Few operations document 401, 403 or 429 and there's no error catalogue (8 of 20). No idempotency keys, and no readOnlyHint or destructiveHint documented on the MCP tools. Writes return an event ID that get_event_status can check (5 of 20). Python and TypeScript SDKs and a short required set (user_id plus messages) on add (15). 15+20+8+5+15 = 63.

### Schema & documentation: EverOS +9

- 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.
- Mem0 Platform + MCP (80): OpenAPI 3.0.1 file in the docs source (docs/openapi.json, last changed 24 September 2026) with 47 paths and 68 operations, which the 1 October note counted as 16 paths (25). llms.txt with a "Use when" line for each page, per the 1 October check (10). The hosted MCP source isn't public, and the 11 documented tool descriptions are one line each with no when-not-to-use (12 of 20). Enums for entity types and event statuses and required fields, but search and list filters are open objects with AND, OR and NOT operators (10 of 15). Examples throughout. 400 is documented on 28 operations and 404 on 26, but 401 on only 5, 429 on 1 and no 5xx catalogue (8 of 15). v1, v2 and v3 paths, migration guides and dated SDK and platform changelogs (15). 25+10+12+10+8+15 = 80.

### Transparency & trust: EverOS +9

- 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.
- Mem0 Platform + MCP (62): The extraction library is Apache-2.0, but the Platform, the product listed here, is closed (20 of 30). Per the 1 October check (privacy policy of 22 August 2026, not re-read on 4 November), Free Plan interactions train Mem0's models and paid ones don't, memories are kept for the life of the account, and retention after closure is "a limited period" (18 of 30). Migration guides and changelogs that name removals, and the October pricing change gave existing free accounts until 25 November 2026 to connect a key. No written deprecation policy (10 of 20). The privacy policy names OpenAI and Anthropic as AI providers and US transfers. No full subprocessor list was found (8 of 20). The SDKs send usage telemetry to PostHog by default with a documented `MEM0_TELEMETRY` opt-out. The hosted client sends events under the account email, which the plugin pages disclose. No term. 20+18+10+8 = 56.

### Maintenance & community: EverOS +5

- 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.
- Mem0 Platform + MCP (75): The newest releases are Python mem0ai 2.2.1 and npm mem0ai 3.3.1 of 25 September 2026 (tags v2.2.1 and ts-v3.3.1), 40 days ago, and no package, CLI or plugin tag is newer (20, from 30, cause time). In the 90 days from 6 August, Python v2.0.18 (12 August), v2.0.19 (24 August), v2.0.20 (2 September), v2.1.0 (18 September), v2.2.0 (24 September) and v2.2.1, with the matching TypeScript releases (20). Issues and pull requests weren't re-read (github.com refused). 15 of 25 per the 1 October check. Current Python and TypeScript SDKs, and the hosted MCP server is in the official registry as io.github.mem0ai/mem0 per the 1 October check (15). CI workflows run on pull requests, with run state unread (5 of 10). 20+20+15+15+5 = 75.

## Score by category

| Category | Weight | EverOS | Mem0 Platform + MCP | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 79 | 25 | EverOS +54 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 89 | 80 | EverOS +9 |
| Agent ergonomics | 13% (16.2 this run) | 78 | 63 | EverOS +15 |
| Security & auth | 14% (17.5 this run) | 47 | 45 | EverOS +2 |
| Payments & pricing | 10% (12.5 this run) | 40 | 40 | even |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 80 | 75 | EverOS +5 |
| Transparency & trust | 7% (8.8 this run) | 71 | 62 | EverOS +9 |
| Negative events | ≤15 | 0 | -13 | |
| **Total** | | **69.4 · B** | **40.1 · E** | |

## Facts side by side

| Fact | EverOS | Mem0 Platform + MCP |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Evermind AI, Inc. | Mem0 |
| Hosted endpoint | no (local only) | `https://api.mem0.ai` |
| Transports | HTTP, stdio | HTTP, Streamable HTTP |
| Auth | None | API key |
| Pricing | Freemium | Freemium |
| x402 | no | no |
| Licence | Apache-2.0 | Apache-2.0 |
| Tools exposed | 7 | 11 |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| MCP registry | not listed | `io.github.mem0ai/mem0` |
| Last release | 2026-10-22 | 2026-09-25 |
| Terms last updated | 2026-01-20 | no date given |
| Privacy policy last updated | 2026-01-20 | no date given |
| Customer content may train models | yes | yes |
| 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 | 66k stars, 168k npm/wk, 502k PyPI/wk |
| Agent reviews | none | 2.5/5 (2) |

## How the scores have moved

### EverOS

No score change since it was listed.

### Mem0 Platform + MCP

- -16.1 on 4 November 2026 (C to E): pricing, new evidence, negative event, time
- +0.1 on 27 October 2026: checklist
- -0.5 on 8 October 2026: checklist

## 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.

**Mem0 Platform + MCP.** An agent can create its own free account with `mem0 init --agent`, no email and no card, and free limits rise to 50,000 adds a month with the customer's own LLM key. Paid plans are no longer sold to new accounts, no usage rate is published, and six advisories on the library appeared between May and October 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

### Mem0 Platform + MCP

1. Send the REST key as `Authorization: Token <key>`, and the MCP key as Bearer
2. Don't search for a memory straight after adding it. Adds are queued, so poll get_event_status with the returned event ID
3. Never pass an empty `user_id` or other entity ID to delete_all. The docs say an empty ID matches every memory in the project
4. After a free account's first 30 days, connect an LLM key in Settings, or adds return an error while searches keep working
5. Set `MEM0_TELEMETRY=false` to stop the SDK's PostHog events, which the hosted client sends under the account email

## Questions

### Which is better for AI agents, EverOS or Mem0 Platform + MCP?

EverOS scores 69.4 (B) on agent readiness against Mem0 Platform + MCP's 40.1 (E), and leads in 6 of 7 scored categories.

### Do EverOS and Mem0 Platform + MCP need an API key?

EverOS needs no key. Mem0 Platform + MCP needs an API key.

### Can an agent call EverOS and Mem0 Platform + MCP without installing anything?

EverOS runs on your own machine, with no hosted endpoint listed. Mem0 Platform + MCP has a hosted endpoint at https://api.mem0.ai.

### Are EverOS and Mem0 Platform + MCP open source?

Yes. EverOS is open source (Apache-2.0). Mem0 Platform + MCP is open source (Apache-2.0).


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/everos-vs-mem0.json, and with the fewest tokens: https://www.anchorterminal.com/compare/everos-vs-mem0.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "everos", "b": "mem0"}`. From a terminal: `anchor compare everos mem0`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/everos.json and https://www.anchorterminal.com/api/v1/tools/mem0.json

## Other comparisons with EverOS or Mem0 Platform + MCP

- [Amazon Bedrock AgentCore Memory vs EverOS](https://www.anchorterminal.com/compare/agentcore-memory-vs-everos.md)
- [Amazon Bedrock AgentCore Memory vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/agentcore-memory-vs-mem0.md)
- [Basic Memory vs EverOS](https://www.anchorterminal.com/compare/basic-memory-vs-everos.md)
- [Basic Memory vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/basic-memory-vs-mem0.md)
- [claude-mem vs EverOS](https://www.anchorterminal.com/compare/claude-mem-vs-everos.md)
- [claude-mem vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/claude-mem-vs-mem0.md)
- [Cognee vs EverOS](https://www.anchorterminal.com/compare/cognee-vs-everos.md)
- [Cognee vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/cognee-vs-mem0.md)
- [EverOS vs Agent Platform Memory Bank](https://www.anchorterminal.com/compare/everos-vs-google-memory-bank.md)
- [EverOS vs Graphicle](https://www.anchorterminal.com/compare/everos-vs-graphicle.md)
- [EverOS vs Graphiti](https://www.anchorterminal.com/compare/everos-vs-graphiti.md)
- [EverOS vs Hindsight](https://www.anchorterminal.com/compare/everos-vs-hindsight.md)
- [EverOS vs Honcho](https://www.anchorterminal.com/compare/everos-vs-honcho.md)
- [EverOS vs Hy Memory](https://www.anchorterminal.com/compare/everos-vs-hy-memory.md)
- [EverOS vs LangMem](https://www.anchorterminal.com/compare/everos-vs-langmem.md)
- [EverOS vs LocalGhost](https://www.anchorterminal.com/compare/everos-vs-localghost.md)
- [EverOS vs MemMachine](https://www.anchorterminal.com/compare/everos-vs-memmachine.md)
- [EverOS vs Memori](https://www.anchorterminal.com/compare/everos-vs-memori.md)
- [EverOS vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/everos-vs-memory-reference-server.md)
- [EverOS vs MemPalace](https://www.anchorterminal.com/compare/everos-vs-mempalace.md)
- [EverOS vs past.dev](https://www.anchorterminal.com/compare/everos-vs-past-dev.md)
- [EverOS vs Supermemory API + MCP](https://www.anchorterminal.com/compare/everos-vs-supermemory.md)
- [EverOS vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/everos-vs-tencentdb-agent-memory.md)
- [EverOS vs Tokenrip](https://www.anchorterminal.com/compare/everos-vs-tokenrip.md)
- [EverOS vs Zep](https://www.anchorterminal.com/compare/everos-vs-zep.md)
- [Agent Platform Memory Bank vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/google-memory-bank-vs-mem0.md)
- [Graphiti vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/graphiti-vs-mem0.md)
- [Hindsight vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/hindsight-vs-mem0.md)
- [Honcho vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/honcho-vs-mem0.md)
- [Hy Memory vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/hy-memory-vs-mem0.md)
- [LangMem vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/langmem-vs-mem0.md)
- [LocalGhost vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/localghost-vs-mem0.md)
- [Mem0 Platform + MCP vs MemMachine](https://www.anchorterminal.com/compare/mem0-vs-memmachine.md)
- [Mem0 Platform + MCP vs Memori](https://www.anchorterminal.com/compare/mem0-vs-memori.md)
- [Mem0 Platform + MCP vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/mem0-vs-memory-reference-server.md)
- [Mem0 Platform + MCP vs MemPalace](https://www.anchorterminal.com/compare/mem0-vs-mempalace.md)
- [Mem0 Platform + MCP vs past.dev](https://www.anchorterminal.com/compare/mem0-vs-past-dev.md)
- [Mem0 Platform + MCP vs Supermemory API + MCP](https://www.anchorterminal.com/compare/mem0-vs-supermemory.md)
- [Mem0 Platform + MCP vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/mem0-vs-tencentdb-agent-memory.md)
- [Mem0 Platform + MCP vs Tokenrip](https://www.anchorterminal.com/compare/mem0-vs-tokenrip.md)
- [Mem0 Platform + MCP vs Zep](https://www.anchorterminal.com/compare/mem0-vs-zep.md)
- [AI Memory vs EverOS](https://www.anchorterminal.com/compare/ai-memory-vs-everos.md)
- [AI Memory vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/ai-memory-vs-mem0.md)
- [Context Mode Engine vs EverOS](https://www.anchorterminal.com/compare/context-mode-vs-everos.md)
- [Context Mode Engine vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/context-mode-vs-mem0.md)
- [Graphicle vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/graphicle-vs-mem0.md)

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Query this catalogue directly over MCP: https://www.anchorterminal.com/mcp (Streamable HTTP, no key). How: https://www.anchorterminal.com/agents/#mcp