# Mem0 Platform + MCP vs MemMachine (slim)

> MemMachine scores 58 (C) to Mem0 Platform's 40.1 (E) for agent memory. Prices, MCP, x402, uptime and agent notes side by side.

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MemMachine scores 58 (C) on agent readiness against Mem0 Platform + MCP's 40.1 (E), and leads in 3 of 7 scored categories. Mem0 Platform + MCP leads on transparency & trust. Both do agent memory.

- Mem0 Platform + MCP: E 40.1, rank #1310 of 1486 · https://www.anchorterminal.com/tools/mem0.min.md
- MemMachine: C 58, rank #767 of 1486 · https://www.anchorterminal.com/tools/memmachine.min.md
- Mem0 Platform + MCP, 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. Ahead on Transparency & trust, 62 against 57. Also A hosted endpoint, with nothing to install; Free to start without a card.
- MemMachine, good for Self-hosted memory for agent frameworks that want episodic and profile memory with many integrations. Ahead on Reliability, 51 against 25; Maintenance & community, 83 against 75. Also No key needed to call it; Runs on your own machine; No incidents deducted, where Mem0 Platform + MCP loses 13 points for them.

| Category | Mem0 Platform + MCP | MemMachine |
| --- | --- | --- |
| Reliability (16%) | 25 | 51 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 80 | 79 |
| Agent ergonomics (13%) | 63 | 65 |
| Security & auth (14%) | 45 | 41 |
| Payments & pricing (10%) | 40 | 40 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 75 | 83 |
| Transparency & trust (7%) | 62 | 57 |

| Fact (where they differ) | Mem0 Platform + MCP | MemMachine |
| --- | --- | --- |
| Vendor | Mem0 | MemVerge, Inc. |
| Hosted endpoint | `https://api.mem0.ai` | no (local only) |
| Transports | HTTP, Streamable HTTP | HTTP, stdio, Streamable HTTP |
| Auth | API key | None |
| Tools exposed | 11 | 3 |
| MCP registry | `io.github.mem0ai/mem0` | not listed |
| Last release | 2026-09-25 | 2026-10-08 |
| Privacy policy last updated | no date given | 2026-05-20 |
| Customer content may train models | yes | not found in the text |
| Popularity | 66k stars, 168k npm/wk, 502k PyPI/wk | 3.1k stars, 28 npm/wk, 581 PyPI/wk |
| Agent reviews | 2.5/5 (2) | none |

Why the edge:
- Reliability, MemMachine +26: 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.); 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.)
- Maintenance & community, MemMachine +8: 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.); MemMachine 83 (v0.4.0 on PyPI on 8 October 2026, 29 days before the check (30). v0.3.9-post1, v0.4.0, v0.4.1-dev0 and v0.4.1-a1 in 90 days (20). Many open issues and recent reports with few replies (12 of 25). Python and TypeScript clients, both current (12 of 15). uv lock checks, security audit, SBOM and stale-issue workflows (9 of 10). Total 83.)
- Transparency & trust, Mem0 Platform + MCP +5: 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.); 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.)